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pneumonia</title> <meta name="description" content="Search results for: pneumonia"> <meta name="keywords" content="pneumonia"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="pneumonia"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 193</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: pneumonia</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">193</span> Determining the Frequency of Pneumonia Emerging in COVID-19 Infection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zoirov%20Amirdin%20Olimovich">Zoirov Amirdin Olimovich</a>, <a href="https://publications.waset.org/abstracts/search?q=Akbarov%20Elbek%20Elmurodovich"> Akbarov Elbek Elmurodovich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Pneumonia that occurs during COVID-19 infection is common among patients. This research was conducted to determine the frequency of symptoms occurring during pneumonia according to the purpose. Objective and Task: The goal of our research is to develop clinical concepts of pneumonia that occur during COVID-19 infection. Our main task is to analyze the results of blood tests and understand the progression of the disease. Research Materials and Methods: The research was conducted among patients admitted to the Tashkent Medical Academy multi-profile clinic in the department of infectious diseases undergoing stationary treatment with a diagnosis of COVID-19. The analyzed patients had an average age of 46, with a total of 48 patients, 23 of whom were female and 25 were male. Research Results: The research results showed the development of pneumonia within three days in 27 patients after COVID-19 infection. During the observation period, 24 patients (88.8%) recovered completely. The X-ray revealed no signs of pneumonia in those who fully recovered. The remaining three patients showed a persistent form of pneumonia. Conclusion: The conclusion of the research indicates that pneumonia during COVID-19 infection develops in many patients, and 88.8% of patients recover completely without any lingering symptoms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title="COVID-19">COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumonia" title=" pneumonia"> pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20X-ray" title=" the X-ray"> the X-ray</a>, <a href="https://publications.waset.org/abstracts/search?q=blood" title=" blood"> blood</a>, <a href="https://publications.waset.org/abstracts/search?q=TTA" title=" TTA"> TTA</a> </p> <a href="https://publications.waset.org/abstracts/177500/determining-the-frequency-of-pneumonia-emerging-in-covid-19-infection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/177500.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">63</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">192</span> Primary Cryptococcal Pneumonia in an HIV Positive Filipino Patient</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mark%20Andrew%20Tu">Mark Andrew Tu</a>, <a href="https://publications.waset.org/abstracts/search?q=Raymond%20Olazo"> Raymond Olazo</a>, <a href="https://publications.waset.org/abstracts/search?q=Cybele%20Abad"> Cybele Abad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cryptococcosis is an invasive infection most commonly found in patients who are immuno compromised. However, patients with this infection usually present with meningitis and rarely pulmonary infection in isolation. We present a case of a Filipino HIV patient who developed cryptococcal pneumonia without meningitis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cryptococcal%20Pneumonia" title="Cryptococcal Pneumonia">Cryptococcal Pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=HIV" title=" HIV"> HIV</a>, <a href="https://publications.waset.org/abstracts/search?q=Filipino" title=" Filipino"> Filipino</a>, <a href="https://publications.waset.org/abstracts/search?q=immune%20system" title=" immune system "> immune system </a> </p> <a href="https://publications.waset.org/abstracts/18964/primary-cryptococcal-pneumonia-in-an-hiv-positive-filipino-patient" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18964.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">441</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">191</span> Design of a Pneumonia Ontology for Diagnosis Decision Support System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sabrina%20Azzi">Sabrina Azzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Michal%20Iglewski"> Michal Iglewski</a>, <a href="https://publications.waset.org/abstracts/search?q=V%C3%A9ronique%20Nabelsi"> Véronique Nabelsi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diagnosis error problem is frequent and one of the most important safety problems today. One of the main objectives of our work is to propose an ontological representation that takes into account the diagnostic criteria in order to improve the diagnostic. We choose pneumonia disease since it is one of the frequent diseases affected by diagnosis errors and have harmful effects on patients. To achieve our aim, we use a semi-automated method to integrate diverse knowledge sources that include publically available pneumonia disease guidelines from international repositories, biomedical ontologies and electronic health records. We follow the principles of the Open Biomedical Ontologies (OBO) Foundry. The resulting ontology covers symptoms and signs, all the types of pneumonia, antecedents, pathogens, and diagnostic testing. The first evaluation results show that most of the terms are covered by the ontology. This work is still in progress and represents a first and major step toward a development of a diagnosis decision support system for pneumonia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Clinical%20decision%20support%20system" title="Clinical decision support system">Clinical decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=Diagnostic%20errors" title=" Diagnostic errors"> Diagnostic errors</a>, <a href="https://publications.waset.org/abstracts/search?q=Ontology" title=" Ontology"> Ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=Pneumonia" title=" Pneumonia"> Pneumonia</a> </p> <a href="https://publications.waset.org/abstracts/88337/design-of-a-pneumonia-ontology-for-diagnosis-decision-support-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88337.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">188</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">190</span> Effects of Clinical Practice Guideline on Knowledge and Preventive Practices of Nursing Personnel and Incidences of Ventilator-associated Pneumonia Thailand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Phawida%20Wattanasoonthorn">Phawida Wattanasoonthorn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ventilator-associated pneumonia is a serious infection found to be among the top three infections in the hospital. To investigate the effects of clinical practice guideline on knowledge and preventive practices of nursing personnel, and incidences of ventilator-associated pneumonia. A pre-post quasi-experimental study on 17 professional nurses, and 123 ventilator-associated pneumonia patients admitted to the surgical intensive care unit, and the accident and surgical ward of Songkhla Hospital from October 2013 to January 2014. The study found that after using the clinical practice guideline, the subjects’ median score increased from 16.00 to 19.00. The increase in practicing correctly was from 66.01 percent to 79.03 percent with the statistical significance level of .05, and the incidences of ventilator-associated pneumonia decreased by 5.00 percent. The results of this study revealed that the use of the clinical practice guideline helped increase knowledge and practice skill of nursing personnel, and decrease incidences of ventilator-associated pneumonia. Thus, nursing personnel should be encouraged, reminded and promoted to continue using the practice guideline through various means including training, providing knowledge, giving feedback, and putting up posters to remind them of practicing correctly and sustainably. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Clinical%20Practice%20Guideline" title="Clinical Practice Guideline">Clinical Practice Guideline</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge" title=" knowledge"> knowledge</a>, <a href="https://publications.waset.org/abstracts/search?q=Preventive%20Ventilator" title=" Preventive Ventilator"> Preventive Ventilator</a>, <a href="https://publications.waset.org/abstracts/search?q=Pneumonia" title=" Pneumonia "> Pneumonia </a> </p> <a href="https://publications.waset.org/abstracts/23403/effects-of-clinical-practice-guideline-on-knowledge-and-preventive-practices-of-nursing-personnel-and-incidences-of-ventilator-associated-pneumonia-thailand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23403.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">410</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">189</span> Optimizing Pediatric Pneumonia Diagnosis with Lightweight MobileNetV2 and VAE-GAN Techniques in Chest X-Ray Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shriya%20Shukla">Shriya Shukla</a>, <a href="https://publications.waset.org/abstracts/search?q=Lachin%20Fernando"> Lachin Fernando</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pneumonia" title="pneumonia">pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=MobileNetV2" title=" MobileNetV2"> MobileNetV2</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20classification" title=" image classification"> image classification</a>, <a href="https://publications.waset.org/abstracts/search?q=GAN" title=" GAN"> GAN</a>, <a href="https://publications.waset.org/abstracts/search?q=VAE" title=" VAE"> VAE</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a> </p> <a href="https://publications.waset.org/abstracts/181598/optimizing-pediatric-pneumonia-diagnosis-with-lightweight-mobilenetv2-and-vae-gan-techniques-in-chest-x-ray-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181598.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">125</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">188</span> A Comparative Study on Deep Learning Models for Pneumonia Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hichem%20Sassi">Hichem Sassi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumonia" title=" pneumonia"> pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=models" title=" models"> models</a>, <a href="https://publications.waset.org/abstracts/search?q=comparative%20study" title=" comparative study"> comparative study</a> </p> <a href="https://publications.waset.org/abstracts/179384/a-comparative-study-on-deep-learning-models-for-pneumonia-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179384.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">64</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">187</span> The Risk of Post-stroke Pneumonia and Its One-Year Disability in Taiwan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hui-Chi%20Huang">Hui-Chi Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Su-Ju%20Yang"> Su-Ju Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ching-Wei%20Lin"> Ching-Wei Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jui-Yao%20Tsai"> Jui-Yao Tsai</a>, <a href="https://publications.waset.org/abstracts/search?q=Liang-Yiang"> Liang-Yiang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Evidence exists that pneumonia is a frequently encountered complication after stroke which is associated with a higher rate of mortality and increased long-term disability Purpose: To determine the predictors associated with the risk of one-year disability in acute stroke. Methods: Data for this longitudinal follow-up study were extracted from a tertiary referral medical center’s stroke registry database in Northern Taipei. Eligible patients with acute stroke admitted to the hospital and completed a one-year follow up were recruited for analysis. Favorable outcome was defined as a modified Rankin Scale score ≤ 2. SAS version 9.2 was used for the multivariable regression analyses to examine the factors correlated with the one-year disability in stroke patients. Results: From January 2012 to December 2013, a total of 1373 (mean age: 70.49±15.4 years, 913(66.5%) males) consecutively administered acute stroke patients were recruited. Overall, the rate of one-year disability was 37.20%(404/1086) in those without post-stroke pneumonia. It increased to 82.93 %(238/287) in patients developed post-stroke pneumonia. Factors associated with increased risk of disability were age ≧ 75(OR= 4.845, p<.0001), female /gender (OR=1.568, p =.0062), previous stroke (OR= 1.868, p = <. 0001) ,dementia (OR= 2.872, p =.0047), ventilator use (OR= 4.653, p <. 0001),age ≧ 75 /pneumonia (OR=1.236, p <. 0001) , ICU admission (OR=3.314, p <.0001) , nasogastric tube insertion (OR= 4.28, p <.0001), speech therapy (OR= 1.79, p =.0142), urinary tract infection (OR= 1.865, p =.0018), estimated glomerular filtration rate (eGFR > 60 )(OR= 0.525, p= .0029), Admission NIHSS >11 (OR= 2.101, p = .0099), Length of hospitalization > 30(d) (OR= 5.182, p <.0001). Conclusion: Older age, severe neurological deficit, complications, rehabilitation intervention, length of hospitalization >30(d), and cognitive impairment were significantly associated with Post-stroke functional impairment, especially those with post-stroke pneumonia. These findings could open new avenues in the management of stroke patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stroke" title="stroke">stroke</a>, <a href="https://publications.waset.org/abstracts/search?q=risk" title=" risk"> risk</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumonia" title=" pneumonia"> pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=disability" title=" disability"> disability</a> </p> <a href="https://publications.waset.org/abstracts/52563/the-risk-of-post-stroke-pneumonia-and-its-one-year-disability-in-taiwan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52563.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">231</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">186</span> Modeling and Optimal Control of Pneumonia Disease with Cost Effective Strategies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getachew%20Tilahun">Getachew Tilahun</a>, <a href="https://publications.waset.org/abstracts/search?q=Oluwole%20Makinde"> Oluwole Makinde</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Malonza"> David Malonza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose and analyze a non-linear mathematical model for the transmission dynamics of pneumonia disease in a population of varying size. The deterministic compartmental model is studied using stability theory of differential equations. The effective reproduction number is obtained and also the local and global asymptotically stability conditions for the disease free and as well as for the endemic equilibria are established. The model exhibit a backward bifurcation and the sensitivity indices of the basic reproduction number to the key parameters are determined. Using Pontryagin’s maximum principle, the optimal control problem is formulated with three control strategies; namely disease prevention through education, treatment and screening. The cost effectiveness analysis of the adopted control strategies revealed that the combination of prevention and treatment is the most cost effective intervention strategies to combat the pneumonia pandemic. Numerical simulation is performed and pertinent results are displayed graphically. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cost%20effectiveness%20analysis" title="cost effectiveness analysis">cost effectiveness analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumonia%20dynamics" title=" pneumonia dynamics"> pneumonia dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=stability%20analysis" title=" stability analysis"> stability analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20simulation" title=" numerical simulation"> numerical simulation</a> </p> <a href="https://publications.waset.org/abstracts/61514/modeling-and-optimal-control-of-pneumonia-disease-with-cost-effective-strategies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61514.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">326</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">185</span> Improving Patient Outcomes for Aspiration Pneumonia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mary%20Farrell">Mary Farrell</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Soubra"> Maria Soubra</a>, <a href="https://publications.waset.org/abstracts/search?q=Sandra%20Vega"> Sandra Vega</a>, <a href="https://publications.waset.org/abstracts/search?q=Dorothy%20Kakraba"> Dorothy Kakraba</a>, <a href="https://publications.waset.org/abstracts/search?q=Joanne%20Fontanilla"> Joanne Fontanilla</a>, <a href="https://publications.waset.org/abstracts/search?q=Moira%20Kendra"> Moira Kendra</a>, <a href="https://publications.waset.org/abstracts/search?q=Danielle%20Tonzola"> Danielle Tonzola</a>, <a href="https://publications.waset.org/abstracts/search?q=Stephanie%20Chiu"> Stephanie Chiu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pneumonia is the most common infectious cause of hospitalizations in the United States, with more than one million admissions annually and costs of $10 billion every year, making it the 8th leading cause of death. Aspiration pneumonia is an aggressive type of pneumonia that results from inhalation of oropharyngeal secretions and/or gastric contents and is preventable. The authors hypothesized that an evidence-based aspiration pneumonia clinical care pathway could reduce 30-day hospital readmissions and mortality rates, while improving the overall care of patients. We conducted a retrospective chart review on 979 patients discharged with aspiration pneumonia from January 2021 to December 2022 at Overlook Medical Center. The authors identified patients who were coded with aspiration pneumonia and/or stable sepsis. Secondarily, we identified 30-day readmission rates for aspiration pneumonia from a SNF. The Aspiration Pneumonia Clinical Care Pathway starts in the emergency department (ED) with the initiation of antimicrobials within 4 hours of admission and early recognition of aspiration. Once this is identified, a swallow test is initiated by the bedside nurse, and if the patient demonstrates dysphagia, they are maintained on strict nothing by mouth (NPO) followed by a speech and language pathologist (SLP) referral for an appropriate modified diet recommendation. Aspiration prevention techniques included the avoidance of straws, 45-degree positioning, no talking during meals, taking small bites, placement of the aspiration wrist band, and consuming meals out of the bed in a chair. Nursing education was conducted with a newly created online learning module about aspiration pneumonia. The authors identified 979 patients, with an average age of 73.5 years old, who were diagnosed with aspiration pneumonia on the index hospitalization. These patients were reviewed for a 30-day readmission for aspiration pneumonia or stable sepsis, and mortality rates from January 2021 to December 2022 at Overlook Medical Center (OMC). The 30-day readmission rates were significantly lower in the cohort that received the clinical care pathway (35.0% vs. 27.5%, p = 0.011). When evaluating the mortality rates in the pre and post intervention cohort the authors discovered the mortality rates were lower in the post intervention cohort (23.7% vs 22.4%, p = 0.61) Mortality among non-white (self-reported as non-white) patients were lower in the post intervention cohort (34.4% vs. 21.0% , p = 0.05). Patients who reported as a current smoker/vaper in the pre and post cohorts had increased mortality rates (5.9% vs 22%). There was a decrease in mortality for the male population but an increase in mortality for women in the pre and post cohorts (19% vs. 25%). The authors attributed this increase in mortality in the post intervention cohort to more active smokers, more former smokers, and more being admitted from a SNF. This research identified that implementation of an Aspiration Pneumonia Clinical Care Pathway showed a statistically significant decrease in readmission rates and mortality rates in non-whites. The 30-day readmission rates were lower in the cohort that received the clinical care pathway (35.0% vs. 27.5%, p = 0.011). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aspiration%20pneumonia" title="aspiration pneumonia">aspiration pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=mortality" title=" mortality"> mortality</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20improvement" title=" quality improvement"> quality improvement</a>, <a href="https://publications.waset.org/abstracts/search?q=30-day%20pneumonia%20readmissions" title=" 30-day pneumonia readmissions"> 30-day pneumonia readmissions</a> </p> <a href="https://publications.waset.org/abstracts/176798/improving-patient-outcomes-for-aspiration-pneumonia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176798.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">62</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">184</span> The Effect of Inhalation of Ylang-ylang Aroma on the Levels of Anxiety of Parents with Hospitalized Toddlers Diagnosed with Pneumonia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Crisostomo%20Hart%20A.">Crisostomo Hart A.</a>, <a href="https://publications.waset.org/abstracts/search?q=Cruz%20Anna%20Cecilia%20R."> Cruz Anna Cecilia R.</a>, <a href="https://publications.waset.org/abstracts/search?q=Cruz%20Bianca%20Isabelle%20A."> Cruz Bianca Isabelle A.</a>, <a href="https://publications.waset.org/abstracts/search?q=Cruz%20John%20Edward%20Ligzurc%20M."> Cruz John Edward Ligzurc M.</a>, <a href="https://publications.waset.org/abstracts/search?q=Cruz%20Mikaela%20Denise%20P."> Cruz Mikaela Denise P. </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aim/purpose: The researchers aimed to determine the effect of Ylang-ylang aroma in decreasing the anxiety levels of parents with hospitalized toddlers diagnosed with pneumonia. Method: Quantitative Quasi-experimental one-group pre-test post-test design was utilized in the study. The study includes a pretest, an intervention, and a posttest on the same experimental group. Participants are parents aged 20 – 35 years old with a hospitalized toddler who is diagnosed with pneumonia. Anxiety levels were measured before the intervention using the State Trait Anxiety Inventory by Spielberger. Those who scored 41-120 proceeded to receive the intervention. The intervention was a 3-day course of aromatherapy where the participants inhaled the Ylang-ylang flower at a distance of 10 – 15 cm away from the face for 10 minutes. The post-test using the same instrument measured the levels of anxiety after the 3-day aromatherapy. Paired T-test of SPSS 21.0 was used to analyze the pre-test and post-test scores. Results: Study yielded a p value of 0.047 which shows significant difference between the levels of anxiety before and after the intervention. Conclusions: Based on the data analysis, the researchers concluded that inhalation of Ylang-ylang aroma is effective in reducing the anxiety level of the parents of hospitalized toddlers diagnosed with Pneumonia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ylang-ylang" title="Ylang-ylang">Ylang-ylang</a>, <a href="https://publications.waset.org/abstracts/search?q=Pneumonia" title=" Pneumonia"> Pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=Toddlers" title=" Toddlers"> Toddlers</a>, <a href="https://publications.waset.org/abstracts/search?q=Aromatherapy" title=" Aromatherapy"> Aromatherapy</a> </p> <a href="https://publications.waset.org/abstracts/20604/the-effect-of-inhalation-of-ylang-ylang-aroma-on-the-levels-of-anxiety-of-parents-with-hospitalized-toddlers-diagnosed-with-pneumonia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20604.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">414</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">183</span> Lung Disease Detection from the Chest X Ray Images Using Various Transfer Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aicha%20Akrout">Aicha Akrout</a>, <a href="https://publications.waset.org/abstracts/search?q=Amira%20Echtioui"> Amira Echtioui</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Ghorbel"> Mohamed Ghorbel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chest%20x-ray" title="chest x-ray">chest x-ray</a>, <a href="https://publications.waset.org/abstracts/search?q=lung%20diseases" title=" lung diseases"> lung diseases</a>, <a href="https://publications.waset.org/abstracts/search?q=transfer%20learning" title=" transfer learning"> transfer learning</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumonia%20detection" title=" pneumonia detection"> pneumonia detection</a> </p> <a href="https://publications.waset.org/abstracts/187213/lung-disease-detection-from-the-chest-x-ray-images-using-various-transfer-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187213.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">42</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">182</span> Effect of Pulmonary Rehabilitation towards Length of Stay and IL-6 Level on Community-Acquired Pneumonia Patients </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Santony%20Santony">Santony Santony</a>, <a href="https://publications.waset.org/abstracts/search?q=Teguh%20Rahayu%20Sartono"> Teguh Rahayu Sartono</a>, <a href="https://publications.waset.org/abstracts/search?q=Iin%20Noor%20Chozin"> Iin Noor Chozin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Pneumonia is acute inflammation on lung parenchyma which is caused by bacteria, virus, fungi, or parasite. In Indonesia, Pneumonia is among the ten inpatient cases. Length of stay is related to the increased morbidity rate, nosocomial infection, and costs. The aim of this study is to assess the effect of pulmonary rehabilitation on the difference in length of stay and the level of Interleukin 6 (IL-6) as an inflammation biomarker for community-acquired pneumonia (CAP) patients in non-intensive rooms. Therefore, pulmonary rehabilitation as adjunctive therapy can be routinely exercised in order to shorten the length of stay, along with the decrease in IL-6 level. Methods: This study was conducted from May to October 2019 at Saiful Anwar General Hospital, Malang. 40 community-acquired pneumonia patients in non-intensive rooms were divided into two groups. 20 patients in the treatment group and 20 patients in the control group, all of them were selected through both inclusion and exclusion criteria. This study used simple consecutive random sampling. In the treatment group, pulmonary rehabilitation performed was composed of breathing exercise, effective coughing technique, clapping (percussion), postural drainage, as well as respiratory muscle training using incentive spirometry device. Pulmonary rehabilitation was conducted twice over five days with a minimum duration of 15 minutes. Blood samples were taken both on the first and the fifth day of the treatment to measure IL-6 level as an inflammation biomarker. Result: For the treatment group, the length of stay was 5.35 days whereas the control group 7.6 days. It can be seen that the treatment group had a shorter length of stay by 2.25 days (P<0,001). The IL-6 level on the first day for the treatment group was 36.27 pg/ml, whereas on the fifth day was 34.36 pg/ml. There was a decrease in IL-6 level on the fifth day of treatment even though it was not statistically significant (P=0.628). IL-6 level on the control group for the first day was 67.76 pg/ml, and after the fifth day, the level decreased to 54.43 pg/ml. There seemed to be a decrease in the IL-6, but it was not statistically significant (P=0.502). On the fifth day, the treatment group showed an average IL-6 level of 34.36 pg/ml. This value was lower than that of the control group which did not receive pulmonary rehabilitation having an IL-6 level of 54.43 pg/ml, even though it was not statistically significant (p=0.221). Conclusion: This study concluded that pulmonary rehabilitation as an adjunctive therapy shortened length of stay by 2.25 days for community-acquired pneumonia patients in a non-intensive room. Both groups experienced a decrease in IL-6 level on the fifth day in comparison with the first day even though it was not statistically significant P>0,05. IL-6 level as an inflammation biomarker decreased on the fifth day of treatment which was in accordance with improvement on pneumonia patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=community-acquired%20pneumonia" title="community-acquired pneumonia">community-acquired pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=interleukin-6" title=" interleukin-6"> interleukin-6</a>, <a href="https://publications.waset.org/abstracts/search?q=length%20of%20stay" title=" length of stay"> length of stay</a>, <a href="https://publications.waset.org/abstracts/search?q=pulmonary%20rehabilitation" title=" pulmonary rehabilitation"> pulmonary rehabilitation</a> </p> <a href="https://publications.waset.org/abstracts/119805/effect-of-pulmonary-rehabilitation-towards-length-of-stay-and-il-6-level-on-community-acquired-pneumonia-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/119805.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">102</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">181</span> Hyponatremia in Community-Acquired Pneumonia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emna%20Ketata">Emna Ketata</a>, <a href="https://publications.waset.org/abstracts/search?q=Wafa%20Farhat"> Wafa Farhat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Hyponatremia is defined by a blood sodium level of ≤ 136 mmol/L; it is associated with a high risk of morbidity and mortality in the emergency room. This was explained by transit disorders, including diarrhea and inappropriate antidiuretic hormone secretion (Syndrome of inappropriate antidiuretic hormone secretion). Pneumonia can cause dyspnea, stress-causing SIADH and digestive symptoms (diarrhea and vomiting). Aim: The purpose of this study was to determine the link between pneumonia and hyponatremia as a predictor of patient’s prognosis and intra-hospital mortality. Methodology: This is a prospective observational study over a period of 3 years in the emergency department. Inclusion :patients (age > 14 years), with clinical signs in favor of pneumonia. Natremia was measured. Natremia was classified as mild to moderate with a blood sodium level between 121 and 135 mmol/L and as severe with a blood sodium level ≤ 120 mmol/L. Results: This study showed an average serum sodium value of 135 mmol/L (range 114–159 mmol/L) in these patients. Hyponatremia was observed in 123 patients (43.6%), 115 patients (97,8%) had mild to moderate hyponatremia and 2,8% had severe hyponatremia. The mean age was 65±17 years with a sex ratio of 1.05. The main reason for consultation in patients with hyponatremia was cough in 58 patients (47.2%), and digestive symptoms were present in 25 patients (20.3. An altered state of consciousness was observed in 11 patients (3%). Patients with hyponatremia had greater heart rate (p=0.02),white blood cell count (p=0.009) , plasmatic lactate (p=0.002) and higher rate of pneumonia recurrence (p=0.001) .In addition, 80% of them have a positive CURB65 score (>=2). hyponatremia had higher rates of use of oxygen therapy compared to patients with normo-natremia (54% vs. 45%). The analytical study showed that hyponatremia is significantly associated with intra-hospital mortality with( p=0.01), severe hyponatremia p=0.04. Conclusion: Hyponatremia is a predictor of mortality and worse prognosis. Recognition of the pathophysiological mechanisms of hyponatremia in pneumonia will probably allow better management of it. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oxygenotherapy" title="oxygenotherapy">oxygenotherapy</a>, <a href="https://publications.waset.org/abstracts/search?q=mortality" title=" mortality"> mortality</a>, <a href="https://publications.waset.org/abstracts/search?q=recurrence" title=" recurrence"> recurrence</a>, <a href="https://publications.waset.org/abstracts/search?q=positif%20curb65" title=" positif curb65"> positif curb65</a> </p> <a href="https://publications.waset.org/abstracts/151161/hyponatremia-in-community-acquired-pneumonia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151161.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">92</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">180</span> Absolute Lymphocyte Count as Predictor of Pneumocystis Pneumonia in Patients With Unknown HIV Status at a Private Tertiary Hospital</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marja%20A.%20Bernardo">Marja A. Bernardo</a>, <a href="https://publications.waset.org/abstracts/search?q=Coreena%20A.%20Bueser"> Coreena A. Bueser</a>, <a href="https://publications.waset.org/abstracts/search?q=Cybele%20Lara%20R.%20Abad"> Cybele Lara R. Abad</a>, <a href="https://publications.waset.org/abstracts/search?q=Raul%20V.%20Destura"> Raul V. Destura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pneumocystis jirovecii pneumonia (PCP) is the most common opportunistic infection among people with HIV. Early consideration of PCP should be made even in patients whose HIV status is unknown as delay in treatment may be fatal. The use of absolute lymphocyte count (ALC) has been suggested as an alternative predictor of PCP especially in resource limited settings where PCR testing is costly or delayed. Objective: To determine whether the absolute lymphocyte count (ALC) can be used as a screening tool to predict Pneumocystis pneumonia in patients with unknown HIV status admitted at a private tertiary hospital. Methods: A retrospective cross-sectional study was conducted at a private tertiary medical center. Inpatient medical records of patients aged 18 years old and above from January 2012 to May 2014, in whom a clinical diagnosis of Pneumocystis jirovecii pneumonia was made were reviewed for inclusion. Demographic data, clinical features, hospital course, PCP PCR and HIV results were recorded. Independent t-test and chi-square analysis was used to determine any statistical difference between PCP-positive and PCP-negative groups. Mann-Whitney U-test was used for comparison of hospital stay. Results: There were no statistically significant differences in baseline characteristics between PCP positive and negative groups. While both the percent lymphocyte count (0.14 ± 0.13 vs 0.21 ± 0.16) and ALC (1160 ± 528.67 vs 1493.70 ± 988.61) were lower for the PCP-positive group, only the percent lymphocyte count reached a statistically significant difference (p= 0.067 vs p= 0.042). Conclusion: A quick determination of the ALC may be useful as an additional parameter to help screen for and diagnose pneumocystis pneumonia. In our study, the ALC of patients with PCP appear to be lower than in patients without PCP. A low ALC (e.g. below 1200) may help with the decision regarding empiric treatment. However, it should be used in conjunction with the patient’s clinical presentation, as well as other diagnostic tests. Larger, prospective studies incorporating the ALC with other clinical predictors are necessary to optimally predict those who would benefit from empiric or expedited management for potential PCP. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pneumocystis%20carinii%20pneumonia" title="Pneumocystis carinii pneumonia">Pneumocystis carinii pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=Absolute%20Lymphocyte%20Count" title=" Absolute Lymphocyte Count"> Absolute Lymphocyte Count</a>, <a href="https://publications.waset.org/abstracts/search?q=infection" title=" infection"> infection</a>, <a href="https://publications.waset.org/abstracts/search?q=PCP" title=" PCP"> PCP</a> </p> <a href="https://publications.waset.org/abstracts/20918/absolute-lymphocyte-count-as-predictor-of-pneumocystis-pneumonia-in-patients-with-unknown-hiv-status-at-a-private-tertiary-hospital" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20918.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">349</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">179</span> Histopathological Examination of Lung Surgery Camel in Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Chitgar">Ali Chitgar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Respiratory infections including diseases in camels are important not only because of the threat of animal health but also to reduce their production. Since that deal with respiratory problems and their treatment requires adequate knowledge of the existing respiratory problems, unfortunately, there is limited information about the species of camels. This study aimed to identify lung lesions camels slaughtered in a slaughterhouse more important was performed using histopathology. Respiratory camels (n = 477) was examined after the killing fully and tissue samples were placed in 10% formalin. The samples and histological sections using hematoxylin and eosin staining and color were evaluated. In this study 79.6 % (236 of 477 samples) of the samples was at least a lung lesion. Rate acute interstitial pneumonia, chronic interstitial pneumonia, bronchopneumonia, bronchiolitis, an inflammation of the pleura and 52.8 % respectively atelectasis (236 of 477 samples), 5.4 % (24 of 477 samples), 7.8 % (35 of 477 samples), 6.7 % (30 of 477 samples), 3.4 % (15 of 477 samples) and 15.2% (68 of 477 samples). The lung lesions, acute interstitial pneumonia and bronchopneumonia in autumn winter rather than spring and summer (p <0/05) and as a result, this study showed that high rates of lung lesions in the camel population. Waste higher results in cold seasons (fall and winter) shows. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=camel" title="camel">camel</a>, <a href="https://publications.waset.org/abstracts/search?q=surgery" title=" surgery"> surgery</a>, <a href="https://publications.waset.org/abstracts/search?q=histopathology" title=" histopathology"> histopathology</a>, <a href="https://publications.waset.org/abstracts/search?q=breathing%20organ" title=" breathing organ"> breathing organ</a> </p> <a href="https://publications.waset.org/abstracts/55173/histopathological-examination-of-lung-surgery-camel-in-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55173.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">203</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">178</span> Hybridization of Manually Extracted and Convolutional Features for Classification of Chest X-Ray of COVID-19</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Bilal%20Ishfaq">M. Bilal Ishfaq</a>, <a href="https://publications.waset.org/abstracts/search?q=Adnan%20N.%20Qureshi"> Adnan N. Qureshi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title="COVID-19">COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20engineering" title=" feature engineering"> feature engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title=" artificial neural networks"> artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=radiology%20images" title=" radiology images"> radiology images</a> </p> <a href="https://publications.waset.org/abstracts/172941/hybridization-of-manually-extracted-and-convolutional-features-for-classification-of-chest-x-ray-of-covid-19" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172941.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">177</span> An Exploration Survival Risk Factors of Stroke Patients at a General Hospital in Northern Taiwan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hui-Chi%20Huang">Hui-Chi Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Su-Ju%20Yang"> Su-Ju Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ching-Wei%20Lin"> Ching-Wei Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jui-Yao%20Tsai"> Jui-Yao Tsai</a>, <a href="https://publications.waset.org/abstracts/search?q=Liang-Yiang"> Liang-Yiang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: The most common serious complication following acute stroke is pneumonia. It has been associated with the increased morbidity, mortality, and medical cost after acute stroke in elderly patients. Purpose: The aim of this retrospective study was to investigate the relationship between stroke patients, risk factors of pneumonia, and one-year survival rates in a group of patients, in a tertiary referal center in Northern Taiwan. Methods: From January 2012 to December 2013, a total of 1730 consecutively administered stroke patients were recruited. The Survival analysis and multivariate regression analyses were used to examine the predictors for the one-year survival in stroke patients of a stroke registry database from northern Taiwan. Results: The risk of stroke mortality increased with age≧ 75 (OR=2.305, p < .0001), cancer (OR=3.221, p=<.0001), stayed in intensive care unit (ICU) (OR=2.28, p <.0006), dysphagia (OR=5.026, p<.0001), without speech therapy(OR=0.192, p < .0001),serum albumin < 2.5(OR=0.322, p=.0053) , eGFR > 60(OR=0.438, p <. 0001), admission NIHSS >11(OR=1.631, p=.0196), length of hospitalization (d) > 30(OR=0.608, p=.0227), and stroke subtype (OR=0.506, p=.0032). After adjustment of confounders, pneumonia was not significantly associated with the risk of mortality. However, it is most likely to develop in patients who are age ≧ 75, dyslipidemia , coronary artery disease , albumin < 2.5 , eGFR <60 , ventilator use , stay in ICU , dysphagia, without speech therapy , urinary tract infection , Atrial fibrillation , Admission NIHSS > 11, length of hospitalization > 30(d) , stroke severity (mRS=3-5) ,stroke Conclusion: In this study, different from previous research findings, we found that elderly age, severe neurological deficit and rehabilitation therapy were significantly associated with Post-stroke Pneumonia. However, specific preventive strategies are needed to target the high risk groups to improve their long-term outcomes after acute stroke. These findings could open new avenues in the management of stroke patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stroke" title="stroke">stroke</a>, <a href="https://publications.waset.org/abstracts/search?q=risk" title=" risk"> risk</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumonia" title=" pneumonia"> pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=survival" title=" survival"> survival</a> </p> <a href="https://publications.waset.org/abstracts/40149/an-exploration-survival-risk-factors-of-stroke-patients-at-a-general-hospital-in-northern-taiwan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40149.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">242</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">176</span> Automatic Classification of Lung Diseases from CT Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abobaker%20Mohammed%20Qasem%20Farhan">Abobaker Mohammed Qasem Farhan</a>, <a href="https://publications.waset.org/abstracts/search?q=Shangming%20Yang"> Shangming Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Al-Nehari"> Mohammed Al-Nehari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CT%20scan" title="CT scan">CT scan</a>, <a href="https://publications.waset.org/abstracts/search?q=Covid-19" title=" Covid-19"> Covid-19</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=lung%20disease%20classification" title=" lung disease classification"> lung disease classification</a> </p> <a href="https://publications.waset.org/abstracts/159935/automatic-classification-of-lung-diseases-from-ct-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159935.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">154</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">175</span> High-Resolution Computed Tomography Imaging Features during Pandemic 'COVID-19'</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sahar%20Heidary">Sahar Heidary</a>, <a href="https://publications.waset.org/abstracts/search?q=Ramin%20Ghasemi%20Shayan"> Ramin Ghasemi Shayan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> By the development of new coronavirus (2019-nCoV) pneumonia, chest high-resolution computed tomography (HRCT) has been one of the main investigative implements. To realize timely and truthful diagnostics, defining the radiological features of the infection is of excessive value. The purpose of this impression was to consider the imaging demonstrations of early-stage coronavirus disease 2019 (COVID-19) and to run an imaging base for a primary finding of supposed cases and stratified interference. The right prophetic rate of HRCT was 85%, sensitivity was 73% for all patients. Total accuracy was 68%. There was no important change in these values for symptomatic and asymptomatic persons. These consequences were besides free of the period of X-ray from the beginning of signs or interaction. Therefore, we suggest that HRCT is a brilliant attachment for early identification of COVID-19 pneumonia in both symptomatic and asymptomatic individuals in adding to the role of predictive gauge for COVID-19 pneumonia. Patients experienced non-contrast HRCT chest checkups and images were restored in a thin 1.25 mm lung window. Images were estimated for the existence of lung scratches & a CT severity notch was allocated separately for each patient based on the number of lung lobes convoluted. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title="COVID-19">COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=radiology" title=" radiology"> radiology</a>, <a href="https://publications.waset.org/abstracts/search?q=respiratory%20diseases" title=" respiratory diseases"> respiratory diseases</a>, <a href="https://publications.waset.org/abstracts/search?q=HRCT" title=" HRCT"> HRCT</a> </p> <a href="https://publications.waset.org/abstracts/143786/high-resolution-computed-tomography-imaging-features-during-pandemic-covid-19" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143786.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">142</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">174</span> Association of Antibiotics Resistance with Efflux Pumps Genes among Multidrug-Resistant Klebsiella pneumonia Recovered from Hospital Waste Water Effluents in Eastern Cape, South Africa</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Okafor%20Joan">Okafor Joan</a>, <a href="https://publications.waset.org/abstracts/search?q=Nwodo%20Uchechukwu"> Nwodo Uchechukwu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Klebsiella pneumoniae (K. pneumoniae) is a significant pathogen responsible for opportunistic and nosocomial infection. One of the most significant antibiotic resistance mechanisms in K. pneumoniae isolates is efflux pumps. Our current study identified efflux genes (AcrAB, OqxAB, MacAB, and TolC) and regulatory genes (RamR and RarA) in multidrug-resistant (MDR) K. pneumoniae isolated from hospital effluents and investigated their relationship with antibiotic resistance. The sum of 145 K. pneumoniae isolates was established by PCR and screened for antibiotic susceptibility. PCR detected efflux pump genes, and their link with antibiotic resistance was statistically examined. However, 120 (83%) of the confirmed isolated were multidrug-resistant, with the largest percentage of resistance to ampicillin (88.3%) and the weakest rate of resistance to imipenem (5.5%). Resistance to the other antibiotics ranged from 11% to 76.6%. Molecular distribution tests show that AcrA, AcrB, MacA, oqxB oqxA, TolC, MacB were detected in 96.7%, 85%, 76.7%, 70.8%, 55.8%, 39.1%, and 29.1% respectively. However, 14.3% of the isolates harboured all seven genes screened. Efflux pump system AcrAB (83.2%) was the most commonly detected in K. pneumonia isolated across all the antibiotics class-tested. In addition, the frequencies of RamR and RarA were 46.2% and 31.4%, respectively. AcrAB and OqxAB efflux pump genes were significantly associated with fluoroquinolone, beta-lactam, carbapenem, and tetracycline resistance (p<0.05). The high rate of efflux genes in this study demonstrated that this resistance mechanism is the dominant way in K. pneumoniae isolates. Appropriate treatment must be used to reduce and tackle the burden of resistant Klebsiella pneumonia in hospital wastewater effluents. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Klebsiella%20pneumonia" title="Klebsiella pneumonia">Klebsiella pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=efflux%20pumps" title=" efflux pumps"> efflux pumps</a>, <a href="https://publications.waset.org/abstracts/search?q=regulatory%20genes" title=" regulatory genes"> regulatory genes</a>, <a href="https://publications.waset.org/abstracts/search?q=multidrug-resistant" title=" multidrug-resistant"> multidrug-resistant</a>, <a href="https://publications.waset.org/abstracts/search?q=hospital" title=" hospital"> hospital</a>, <a href="https://publications.waset.org/abstracts/search?q=PCR" title=" PCR"> PCR</a> </p> <a href="https://publications.waset.org/abstracts/159759/association-of-antibiotics-resistance-with-efflux-pumps-genes-among-multidrug-resistant-klebsiella-pneumonia-recovered-from-hospital-waste-water-effluents-in-eastern-cape-south-africa" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159759.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">84</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">173</span> Obstructive Bronchitis and Pneumonia by a Mixed Infection of HPIV- 3, S. pneumoniae in an Immunocompromised 10M Infant: Case Report</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Olga%20Smilevska%20Spasova">Olga Smilevska Spasova</a>, <a href="https://publications.waset.org/abstracts/search?q=Katerina%20Boshkovska"> Katerina Boshkovska</a>, <a href="https://publications.waset.org/abstracts/search?q=Gorica%20Popova"> Gorica Popova</a>, <a href="https://publications.waset.org/abstracts/search?q=Mirjana%20Popovska"> Mirjana Popovska</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Pneumonia is an infection of the pulmonary parenchyma. HPIV 3 is one of four viruses that is a member of the Paramyxoviridae family designated types 1-4 that have a nonsegmented, single-stranded RNA genome with a lipid-containing envelope. They are spread from the respiratory tract by aerosolized secretions or by direct contact with secretions. Type 3 is endemic and can cause serious illness in immunocompromised patients. Illness caused by parainfluenza occurs shortly after inoculation with the virus. The level of immunoglobulin A antibody in serum is the best predictor of susceptibility to infection. Streptococcus pneumonia or pneumococcus is a Gram-positive, spherical bacteria, usually found in pairs and it is a member of the genus Streptococcus. Streptococcus pneumonia resides asymptomatically in healthy carriers typically colonizing the respiratory tract, sinuses, and nasal cavity. In individuals with weaker immune systems like young infants, pneumococcal bacterium is the most common cause of community-acquired pneumonia in the world. Case Report: The aim is to present a case of lower respiratory tract infection in an infant caused by parainfluenza virus 3, S. pneumonia and undifferentiated gram-negative bacteria that was successfully treated. The infant is with a history of recurrent episodes of wheezing in the past 3mounts.Infant of 10months presents 2weeks before admittance with high fever, runny nose, and cough. The primary pediatrician prescribed oral cefpodoxime for 10days and inhaled salbutamol. Two days before admittance in hospital the infant with high fever, cough, and difficulty breathing. At admittance, infant is pale, anxious with rapid respirations, cough, wheezing and tachycardia. On auscultation: vesicular breathing sounds with high pitched wheezing and on the right coarse crackles. Investigations: Blood analysis: RBC: 4, 7 x1012L, WBC: 8,3x109L: Neut: 42.73% Lym: 41.57%, Hgb: 9.38 g/dl MCV: 62.7fl, MCH: 20.0pg MCHC: 31.8 g/dl RDW: 18.7% Plt-307.9 x109LCRP: 2,5mg/l, serum iron-7.92umol/l, O2sat-97% on blood gas analysis, puls-125/min.X-ray of chest with hyperinflationand right pericardial consolidation. Microbiological analysis of sputum sample is positive for undifferentiated gram-negative bacteria (colonizer)–resistant to cefotaxime, ampicillin, cefoxitin, sulfamet.+trimetoprim and sensitive to amikacin, gentamicin, and ciprofloxacin. Molecular multiplex RT-PCR for 19 viruses and multiplex PCR for 7 bacteria test for respiratory pathogens positive for Parainfluenza virus 3(Ct=22.73), Streptococcus pneumonia (Ct=26.75).IED: IgG-9.31g/l, IgA-0.351g/l, IgM-0.86g/l. Therapy: Treatment was started with inhaled salbutamol, intravenous antibiotic cefotaxime as well as systemic corticosteroids. On day 7 because of slow clinical resolution of chest auscultation findings and an etiologic clue with a positive sputum sample for resistant undifferentiated gram negative bacteria, a second intravenous antibiotic was administered amikacin. The infant is discharged on day 14 with resolution of clinical findings. Conclusion: Mixed co-infections with respiratory viruses and bacteria in immunocompromised infants are likely to lead to a more severe form of community acquired pneumonia that will need hospitalization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HPIV-%203" title="HPIV- 3">HPIV- 3</a>, <a href="https://publications.waset.org/abstracts/search?q=infant" title=" infant"> infant</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumonia" title=" pneumonia"> pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20pneumonia" title=" S. pneumonia"> S. pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=x-ray%20chest" title=" x-ray chest"> x-ray chest</a> </p> <a href="https://publications.waset.org/abstracts/149986/obstructive-bronchitis-and-pneumonia-by-a-mixed-infection-of-hpiv-3-s-pneumoniae-in-an-immunocompromised-10m-infant-case-report" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149986.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">172</span> Policy Implications of Demographic Impacts on COVID-19, Pneumonia, and Influenza Mortality: A Multivariable Regression Approach to Death Toll Reduction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saiakhil%20Chilaka">Saiakhil Chilaka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Understanding the demographic factors that influence mortality from respiratory diseases like COVID-19, pneumonia, and influenza is crucial for informing public health policy. This study utilizes multivariable regression models to assess the relationship between state, sex, and age group on deaths from these diseases using U.S. data from 2020 to 2023. The analysis reveals that age and sex play significant roles in mortality, while state-level variations are minimal. Although the model’s low R-squared values indicate that additional factors are at play, this paper discusses how these findings, in light of recent research, can inform future public health policy, resource allocation, and intervention strategies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title="COVID-19">COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariable%20regression" title=" multivariable regression"> multivariable regression</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20policy" title=" public policy"> public policy</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20science" title=" data science"> data science</a> </p> <a href="https://publications.waset.org/abstracts/191848/policy-implications-of-demographic-impacts-on-covid-19-pneumonia-and-influenza-mortality-a-multivariable-regression-approach-to-death-toll-reduction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191848.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">20</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">171</span> Pattern of Bacterial Isolates and Antimicrobial Resistance at Ayder Comprehensive Specialized Referral Hospital in Northern Ethiopia: A Retrospective Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Solomon%20Gebremariam">Solomon Gebremariam</a>, <a href="https://publications.waset.org/abstracts/search?q=Mulugeta%20Naizigi"> Mulugeta Naizigi</a>, <a href="https://publications.waset.org/abstracts/search?q=Aregawi%20Haileselassie"> Aregawi Haileselassie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Knowledge of the pattern of bacterial isolates and their antimicrobial susceptibility is crucial for guiding empirical treatment and infection prevention and control measures. Objective: The aim of this study was to analyze the pattern of bacterial isolates and their susceptibility patterns from various specimens. Methods: Retrospectively, a total of 1067 microbiological culture results that were isolated, characterized, and identified by standard microbiological methods and whose antibiotic susceptibility was determined using CLSI guidelines between 2017 and 2019 were retrieved and analyzed. Data were entered and analyzed using the Stata release 10.1 statistical package. Result: The positivity rate of culture was 26.04% (419/1609). The most common bacteria isolated were S. aureus 23.8% (94), E. coli 15.1% (60), Klebsiella pneumonia 14.1% (56), Pseudomonas aeruginosa 8.5% (34), and CONS 7.3% (29). S. aureus and CONS showed a high (58.1% - 96.2%) rate of resistance to most antibiotics tested. They were less resistant to Vancomycin which is 18.6% (13/70) and 11.8% (2/17), respectively. Similarly, the resistance of E. coli, Klebsella pneumonia, and Pseudomonas aeruginosa was high (69.4% - 100%) to most antibiotics. They were less resistant to Ciprofloxacilin, which is 41.1% (23/56), 19.2% (10/52), and 16.1% (5/31), respectively. Conclusion: This study has shown that there is a high rate of antibiotic resistance among bacterial isolates in this hospital. A combination of Vancomycin and Ciprofloxacin should be considered in the choice of antibiotics for empirical treatment of suspected infections due to S. aureus, CONS, E. coli, Klebsiella pneumonia, Pseudomonas such as in infections within hospital setup. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=antimicrobial" title="antimicrobial">antimicrobial</a>, <a href="https://publications.waset.org/abstracts/search?q=resistance" title=" resistance"> resistance</a>, <a href="https://publications.waset.org/abstracts/search?q=bacteria" title=" bacteria"> bacteria</a>, <a href="https://publications.waset.org/abstracts/search?q=hospital" title=" hospital"> hospital</a> </p> <a href="https://publications.waset.org/abstracts/145896/pattern-of-bacterial-isolates-and-antimicrobial-resistance-at-ayder-comprehensive-specialized-referral-hospital-in-northern-ethiopia-a-retrospective-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145896.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">74</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">170</span> Antımıcrobıal Actıvıty of Gırardınıa Heterophılla</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20S.%20BEDI%2A">P. S. BEDI* </a>, <a href="https://publications.waset.org/abstracts/search?q=Neavty%20Thakur"> Neavty Thakur</a>, <a href="https://publications.waset.org/abstracts/search?q=Balv%C4%B1nder%20S%C4%B1ngh"> Balvınder Sıngh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present study an attempt has been made to prepare the crude extracts of leaves and stem of ‘Girardinia heterophylla’ by using various solvents like petroleum ether, ethanol and double distilled water. The samples were given the code NGLS 1, NGLS 2, NGLS 3, NGSS 1, NGSS 2 and NGSS 3 respectively. All the extracts were used to study their antimicrobial activity against gram positive bacteria eg. Bacillus subtilis, Gram negative bacteria eg. E. coli, K. pneumonia and antifungal activity against Aspergillus niger. The results of the antimicrobial activity showed that all the crude extracts of the plant posseses antibacterial activity. Maximum antibacterial activity was shown by NGLS 2, NGLS 3 and NGSS 3 against K. pneumonia. The growth of fungus A. niger was also inhibited by all the crude extracts. Maximum inhibition was shown by NGSS 2 followed by NGSS 1. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Girardinia%20heterophylla" title="Girardinia heterophylla">Girardinia heterophylla</a>, <a href="https://publications.waset.org/abstracts/search?q=leaves%20and%20stem%20extracts" title=" leaves and stem extracts"> leaves and stem extracts</a>, <a href="https://publications.waset.org/abstracts/search?q=Antibacterial%20activity" title=" Antibacterial activity"> Antibacterial activity</a>, <a href="https://publications.waset.org/abstracts/search?q=antifungal%20activity." title=" antifungal activity."> antifungal activity.</a> </p> <a href="https://publications.waset.org/abstracts/2494/antimicrobial-activity-of-girardinia-heterophilla" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2494.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">345</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">169</span> Effects of Lung Protection Ventilation Strategies on Postoperative Pulmonary Complications After Noncardiac Surgery: A Network Meta-Analysis of Randomized Controlled Trials</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ran%20An">Ran An</a>, <a href="https://publications.waset.org/abstracts/search?q=Dang%20Wang"> Dang Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Mechanical ventilation has been confirmed to increase the incidence of postoperative pulmonary complications (PPCs), and several studies have shown that low tidal volumes combined with positive end-expiratory pressure (PEEP) and recruitment manoeuvres (RM) reduce the incidence of PPCs. However, the optimal lung-protective ventilatory strategy remains unclear. Methods: Multiple databases were searched for randomized controlled trials (RCTs) published prior to October 2023. The association between individual PEEP (iPEEP) or other forms of lung-protective ventilation and the incidence of PPCs was evaluated by Bayesian network meta-analysis. Results: We included 58 studies (11610 patients) in this meta-analysis. The network meta-analysis showed that low ventilation (LVt) combined with iPEEP and RM was associated with significantly lower incidences of PPCs [HVt: OR=0.38 95CrI (0.19, 0.75), LVt: OR=0.33, 95% CrI (0.12, 0.82)], postoperative atelectasis, and pneumonia than was HVt or LVt. In abdominal surgery, LVT combined with iPEEP or medium-to-high PEEP and RM were associated with significantly lower incidences of PPCs, postoperative atelectasis, and pneumonia. LVt combined with iPEEP and RM was ranked the highest, which was based on SUCRA scores. Conclusion: LVt combined with iPEEP and RM decreased the incidences of PPCs, postoperative atelectasis, and pneumonia in noncardiac surgery patients. iPEEP-guided ventilation was the optimal lung protection ventilation strategy. The quality of evidence was moderate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=protection%20ventilation%20strategies" title="protection ventilation strategies">protection ventilation strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=postoperative%20pulmonary%20complications" title=" postoperative pulmonary complications"> postoperative pulmonary complications</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20meta-analysis" title=" network meta-analysis"> network meta-analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=noncardiac%20surgery" title=" noncardiac surgery"> noncardiac surgery</a> </p> <a href="https://publications.waset.org/abstracts/186731/effects-of-lung-protection-ventilation-strategies-on-postoperative-pulmonary-complications-after-noncardiac-surgery-a-network-meta-analysis-of-randomized-controlled-trials" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186731.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">35</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">168</span> Antimicrobial Activity of Some Plant Extracts against Clinical Pathogen and Candida Species</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marwan%20Khalil%20Qader">Marwan Khalil Qader</a>, <a href="https://publications.waset.org/abstracts/search?q=Arshad%20Mohammad%20Abdullah"> Arshad Mohammad Abdullah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Antimicrobial resistance is a major cause of significant morbidity and mortality globally. Seven plant extracts (Plantago mediastepposa, Quercusc infectoria, Punic granatum, Thymus lcotschyana, Ginger officeinals, Rhus angustifolia and Cinnamon) were collected from different regions of Kurdistan region of Iraq. These plants’ extracts were dissolved in absolute ethanol and distillate water, after which they were assayed in vitro as an antimicrobial activity against Candida tropicalis, Candida albicanus, Candida dublinensis, Candida krusei and Candida glabrata also against 2 Gram-positive (Bacillus subtilis and Staphylococcus aureus) and 3 Gram-negative bacteria (Escherichia coli, Pseudomonas aeruginosa and Klebsilla pneumonia). The antimicrobial activity was determined in ethanol extracts and distilled water extracts of these plants. The ethanolic extracts of Q. infectoria showed the maximum activity against all species of Candida fungus. The minimum inhibition zone of the Punic granatum ethanol extracts was 0.2 mg/ml for all microorganisms tested. Klebsilla pneumonia was the most sensitive bacterial strain to Quercusc infectoria and Rhus angustifolia ethanol extracts. Among both Gram-positive and Gram-negative bacteria tested with MIC of 0.2 mg/ml, the minimum inhibition zone of Ginger officeinals D. W. extracts was 0.2 mg/mL against Pseudomonas aeruginosa and Klebsilla pneumonia. The most sensitive bacterial strain to Thymus lcotschyana and Plantago mediastepposa D.W. extracts was S. aureus and E. coli. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=antimicrobial%20activity" title="antimicrobial activity">antimicrobial activity</a>, <a href="https://publications.waset.org/abstracts/search?q=pathogenic%20bacteria" title=" pathogenic bacteria"> pathogenic bacteria</a>, <a href="https://publications.waset.org/abstracts/search?q=plant%20extracts" title=" plant extracts"> plant extracts</a>, <a href="https://publications.waset.org/abstracts/search?q=chemical%20systems%20engineering" title=" chemical systems engineering"> chemical systems engineering</a> </p> <a href="https://publications.waset.org/abstracts/8700/antimicrobial-activity-of-some-plant-extracts-against-clinical-pathogen-and-candida-species" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8700.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">336</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">167</span> HRCT of the Chest and the Role of Artificial Intelligence in the Evaluation of Patients with COVID-19</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Parisa%20Mansour">Parisa Mansour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chest" title="chest">chest</a>, <a href="https://publications.waset.org/abstracts/search?q=HRCT" title=" HRCT"> HRCT</a>, <a href="https://publications.waset.org/abstracts/search?q=covid-19" title=" covid-19"> covid-19</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20HRCT" title=" chest HRCT"> chest HRCT</a> </p> <a href="https://publications.waset.org/abstracts/179600/hrct-of-the-chest-and-the-role-of-artificial-intelligence-in-the-evaluation-of-patients-with-covid-19" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179600.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">63</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">166</span> Multi-Classification Deep Learning Model for Diagnosing Different Chest Diseases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bandhan%20Dey">Bandhan Dey</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhsina%20Bintoon%20Yiasha"> Muhsina Bintoon Yiasha</a>, <a href="https://publications.waset.org/abstracts/search?q=Gulam%20Sulaman%20Choudhury"> Gulam Sulaman Choudhury</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20classification" title=" image classification"> image classification</a>, <a href="https://publications.waset.org/abstracts/search?q=X-ray%20images" title=" X-ray images"> X-ray images</a>, <a href="https://publications.waset.org/abstracts/search?q=Tensorflow" title=" Tensorflow"> Tensorflow</a>, <a href="https://publications.waset.org/abstracts/search?q=Keras" title=" Keras"> Keras</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20diseases" title=" chest diseases"> chest diseases</a>, <a href="https://publications.waset.org/abstracts/search?q=convolutional%20neural%20networks" title=" convolutional neural networks"> convolutional neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-classification" title=" multi-classification"> multi-classification</a> </p> <a href="https://publications.waset.org/abstracts/158065/multi-classification-deep-learning-model-for-diagnosing-different-chest-diseases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158065.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">92</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">165</span> The Use of Respiratory Index of Severity in Children (RISC) for Predicting Clinical Outcomes for 3 Months-59 Months Old Patients Hospitalized with Community-Acquired Pneumonia in Visayas Community Medical Center, Cebu City from January 2013 - June 2</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Karl%20Owen%20L.%20Suan">Karl Owen L. Suan</a>, <a href="https://publications.waset.org/abstracts/search?q=Juliet%20Marie%20S.%20Lambayan"> Juliet Marie S. Lambayan</a>, <a href="https://publications.waset.org/abstracts/search?q=Floramay%20P.%20Salo-Curato"> Floramay P. Salo-Curato</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: To predict the outcome among patients admitted with community-acquired pneumonia (ages 3 months to 59 months old) admitted in Visayas Community Medical Center using the Respiratory Index of Severity in Children (RISC). Design: A cross-sectional study design was used. Setting: The study was done in Visayas Community Medical Center, which is a private tertiary level in Cebu City from January-June 2013. Patients/Participants: A total of 72 patients were initially enrolled in the study. However, 1 patient transferred to another institution, thus 71 patients were included in this study. Within 24 hours from admission, patients were assigned a RISC score. Statistical Analysis: Cohen’s kappa coefficient was used for inter-rater agreement for categorical data. This study used frequency and percentage distribution for qualitative data. Mean, standard deviation and range were used for quantitative data. To determine the relationship of each RISC score parameter and the total RISC score with the outcome, a Mann Whitney U Test and 2x2 Fischer Exact test for testing associations were used. A p value less of than 0.05 alpha was considered significant. Results: There was a statistical significance between RISC score and clinical outcome. RISC score of greater than 4 was correlated with intubation and/or mortality. Conclusion: The RISC scoring system is a simple combination of clinical parameters and a reliable tool that will help stratify patients aged 3 months to 59 months in predicting clinical outcome. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RISC" title="RISC">RISC</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20outcome" title=" clinical outcome"> clinical outcome</a>, <a href="https://publications.waset.org/abstracts/search?q=community-acquired%20pneumonia" title=" community-acquired pneumonia"> community-acquired pneumonia</a>, <a href="https://publications.waset.org/abstracts/search?q=patients" title=" patients "> patients </a> </p> <a href="https://publications.waset.org/abstracts/10188/the-use-of-respiratory-index-of-severity-in-children-risc-for-predicting-clinical-outcomes-for-3-months-59-months-old-patients-hospitalized-with-community-acquired-pneumonia-in-visayas-community-medical-center-cebu-city-from-january-2013-june-2" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10188.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">302</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">164</span> DenseNet and Autoencoder Architecture for COVID-19 Chest X-Ray Image Classification and Improved U-Net Lung X-Ray Segmentation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jonathan%20Gong">Jonathan Gong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=convolutional%20neural%20networks" title=" convolutional neural networks"> convolutional neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/160217/densenet-and-autoencoder-architecture-for-covid-19-chest-x-ray-image-classification-and-improved-u-net-lung-x-ray-segmentation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160217.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=pneumonia&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=pneumonia&page=3">3</a></li> <li class="page-item"><a class="page-link" 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