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action="https://publications.waset.org/abstracts/search"> <div 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="chest x-ray analysis"> <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> 28028</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: chest x-ray analysis</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28028</span> Chest Trauma and Early Pulmonary Embolism: The Risks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vignesh%20Ratnaraj">Vignesh Ratnaraj</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Marascia"> Daniel Marascia</a>, <a href="https://publications.waset.org/abstracts/search?q=Kelly%20Ruecker"> Kelly Ruecker</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: Pulmonary embolism (PE) is a major cause of morbidity and mortality in trauma patients. Data suggests PE is occurring earlier in trauma patients, with attention being turned to possible de novo events. Here, we examine the incidence of early PE at a level 1 trauma center and examine the relationship with a chest injury. Method: A retrospective analysis was performed from a prospective trauma registry at a level 1 trauma center. All patients admitted from 1 January 2010 to 30 June 2019 diagnosed with PE following trauma were included. Early PE was considered a diagnosis within 72 hours of admission. The severity of the chest injury was determined by the Abbreviated Injury Score (AIS). Analysis of severe chest injury and incidence of early PE was performed using chi-square analysis. Sub-analysis on the timing of PE and PE location was also performed using chi-square analysis. Results: Chest injury was present in 125 of 184 patients diagnosed with PE. Early PE occurred in 28% (n=35) of patients with a chest injury, including 24.39% (n=10) with a severe chest injury. Neither chest injury nor severe chest injury determined the presence of early PE (p= > 0.05). Sub-analysis showed a trend toward central clots in early PE (37.14%, n=13) compared to late (27.78%, n=25); however, this was not found to be significant (p= > 0.05). Conclusion: PE occurs early in trauma patients, with almost one-third being diagnosed before 72 hours. This analysis does not support the paradigm that chest injury, nor severe chest injury, results in statistically significant higher rates of early PE. Interestingly, a trend toward early central PE was noted in those suffering chest trauma. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=trauma" title="trauma">trauma</a>, <a href="https://publications.waset.org/abstracts/search?q=PE" title=" PE"> PE</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20injury" title=" chest injury"> chest injury</a>, <a href="https://publications.waset.org/abstracts/search?q=anticoagulation" title=" anticoagulation"> anticoagulation</a> </p> <a href="https://publications.waset.org/abstracts/160319/chest-trauma-and-early-pulmonary-embolism-the-risks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160319.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">101</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">28027</span> The Evaluation of Children Who Had Chest Pain on Pediatric Emergency Department</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sabiha%20Sahin">Sabiha Sahin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Chest pain is a common complaint in children visiting the emergency department (ED). True organic problems like cardiac disease are rare. We assess the etiology of chest pain among children visiting a Pediatric ED in Eskisehir Osmangazi University. Method: We prospectively evaluated of children with chest pain who visited our Pediatric ED between 1 January 2013 and 31 December 2014. Any case of trauma-associated chest pain was excluded from this study. Results: A total of 100 patients (54 boys, 46 girls), mean age: 11,86±3,51 (age range, 6–17 years) were enrolled into this study; 100 patients had chest radiograms (100 %). Pneumonia was identified in 15 patients. All patients had electrocardiogram study (100 %) and 16 of them showed abnormalities. Additional diagnostic tests were performed on all patients including complete blood count analysis, cardiac markers (CK-MB, Troponin I) and lactate (blood gas analysis). Echocardiograms were performed on all patients and 16 of them showed abnormality (five of majör abnormality). Panendoscopy was done in 20 patients, and gastroesophageal reflux was found in 12 (%12). Overall, idiopathic chest pain and myalgia was the most common diagnosis (32 %). Other associated disorders were asthma (12 %), panic attack (13 %). Conclusion: The most common cause of chest pain prompting a child to visit the ED is idiopathic chest pain. Careful physical examination can reveal important clues and save many unnecessary examinations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=child" title="child">child</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20pain" title=" chest pain"> chest pain</a>, <a href="https://publications.waset.org/abstracts/search?q=pediatric%20emergency%20department" title=" pediatric emergency department"> pediatric emergency department</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation" title=" evaluation"> evaluation</a> </p> <a href="https://publications.waset.org/abstracts/47866/the-evaluation-of-children-who-had-chest-pain-on-pediatric-emergency-department" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47866.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">253</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">28026</span> An Autopsy Case of Blunt Chest Trauma from a Traffic Accident Complicated by Chest Compression Due to Resuscitation Attempts</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Satoshi%20Furukawa">Satoshi Furukawa</a>, <a href="https://publications.waset.org/abstracts/search?q=Satomu%20Morita"> Satomu Morita</a>, <a href="https://publications.waset.org/abstracts/search?q=Katsuji%20Nishi"> Katsuji Nishi</a>, <a href="https://publications.waset.org/abstracts/search?q=Masahito%20Hitosugi"> Masahito Hitosugi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Coronary artery dissection leading to acute myocardial infarction after blunt chest trauma is extremely rare. A 67-year-old woman suffered blunt chest trauma following a traffic accident. The electrocardiogram revealed acute posterior ST-segment elevation and myocardial infarction and coronary angiography demonstrated acute right coronary artery dissection. Following the death of the victim an autopsy was performed after cardiopulmonary support had been carried out. In this case report, we describe the case of a woman with blunt chest trauma, who developed an acute myocardial infarction secondary to right coronary artery dissection. Although there was additional the blunt chest trauma due to chest compression, we confirmed the injury at autopsy and by histological findings. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blunt%20chest%20trauma" title="blunt chest trauma">blunt chest trauma</a>, <a href="https://publications.waset.org/abstracts/search?q=right%20coronary%20artery%20dissection" title=" right coronary artery dissection"> right coronary artery dissection</a>, <a href="https://publications.waset.org/abstracts/search?q=coronary%20angiography" title=" coronary angiography"> coronary angiography</a>, <a href="https://publications.waset.org/abstracts/search?q=autopsy" title=" autopsy"> autopsy</a>, <a href="https://publications.waset.org/abstracts/search?q=histological%20examination" title=" histological examination "> histological examination </a> </p> <a href="https://publications.waset.org/abstracts/13624/an-autopsy-case-of-blunt-chest-trauma-from-a-traffic-accident-complicated-by-chest-compression-due-to-resuscitation-attempts" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13624.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">634</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">28025</span> User Satisfaction in Rama-Chest Mouthpiece for Flexible Bronchoscopy in Ramathibodi Hospital</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chariya%20Laohavich">Chariya Laohavich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Some limitations and complications have been found associated with commercial mouthpiece in bronchoscopic procedure. Therefore, we invented the Rama-chest mouthpiece from plastic normal saline bottle. Objective: The aim of this study was to compare user satisfaction in Rama-chest mouthpiece with the commercial mouthpiece. Methods: A prospective randomized controlled trial between commercial mouthpiece and Rama-chest mouthpiece was conducted on patients who were underwent bronchoscopy and required mouthpiece insertion from May to June 2014. The questionnaire about satisfaction was completed by the bronchoscopists, assistant nurses, and patients. Results: Thirty procedures in both groups were investigated. Mean satisfaction scores filled by the bronchoscopists and assistant nurses were not different between both groups. However, higher satisfaction score filled by the patients was found in Rama-chest mouthpiece than the comparator (p=0.011). Complications such as abrasion, pain, and itching were observed in commercial mouthpiece but not found in Rama-chest mouthpiece. Conclusion: We have introduced Rama-chest mouthpiece and proved its usefulness comparable to the commercial mouthpiece. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mouthpiece" title="mouthpiece">mouthpiece</a>, <a href="https://publications.waset.org/abstracts/search?q=bronchoscopist" title=" bronchoscopist"> bronchoscopist</a>, <a href="https://publications.waset.org/abstracts/search?q=bronchology" title=" bronchology"> bronchology</a>, <a href="https://publications.waset.org/abstracts/search?q=pulmonology%20and%20respiratory%20diseases" title=" pulmonology and respiratory diseases"> pulmonology and respiratory diseases</a> </p> <a href="https://publications.waset.org/abstracts/13321/user-satisfaction-in-rama-chest-mouthpiece-for-flexible-bronchoscopy-in-ramathibodi-hospital" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13321.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">366</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">28024</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">28023</span> Chest Pain as a Predictor for Heart Issues in Geriatrics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leila%20Kargar">Leila Kargar</a>, <a href="https://publications.waset.org/abstracts/search?q=Homa%20Abri"> Homa Abri</a>, <a href="https://publications.waset.org/abstracts/search?q=Golsa%20Safai"> Golsa Safai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The occurrence of chest pain among geriatrics could be considered as a predictor of heart issues. There is a need for attention to this pain among this population. This review paper has tried to collect the recent data with attention to the chest pain among geriatrics. This review paper has focused on specific keywords, including chest pain, heart issues, and geriatrics, among published papers from 2015 till 2020. To collect data for this purpose, Scopus, Web of Sciences, and PubMed were used. After inserting related papers to the Endnote, an independent researcher checked the abstract, and papers with unclear methods or non-English language were excluded. Finally, 7-papers were included in this review paper. The findings of those papers showed that chest pain could be a predictor for heart issues, and also, there is a direct relationship between chest pain and heart issues among geriatrics. So, early detection and an accurate decision could be helpful to prevent heart issues in this population. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pain" title="pain">pain</a>, <a href="https://publications.waset.org/abstracts/search?q=heart%20issue" title=" heart issue"> heart issue</a>, <a href="https://publications.waset.org/abstracts/search?q=geriatrics" title=" geriatrics"> geriatrics</a>, <a href="https://publications.waset.org/abstracts/search?q=health" title=" health"> health</a> </p> <a href="https://publications.waset.org/abstracts/140884/chest-pain-as-a-predictor-for-heart-issues-in-geriatrics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140884.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">218</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">28022</span> Acute Asthma in Emergency Department, Prevalence of Respiratory and Non-Respiratory Symptoms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sherif%20Refaat">Sherif Refaat</a>, <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Aref"> Hassan Aref</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Although asthma is a well-identified presentation to the emergency department, little is known about the frequency and percentage of respiratory and non-respiratory symptoms in patients with acute asthma in the emergency department (ED). Objective: The aim of this study is to identify the relationship between acute asthma exacerbation and different respiratory and non-respiratory symptoms including chest pain encountered by patients visiting the emergency department. Subjects and methods: Prospective study included 169 (97 females and 72 males) asthmatic patients who were admitted to emergency department of two tertiary care facility hospitals for asthma exacerbation from the period of September 2010 to August 2013, an anonyms questionnaire was used to collect symptoms and analysis of symptoms. Results: Females were 97 (57%) of the patients, mean age was 35.6 years; dyspnea on exertion was the commonest symptom accounting for 161 (95.2%) of patients, followed by dyspnea at rest 155 (91.7%), wheezing in 152 (89.9%), chest pain was present in 82 patients (48.5%), the pain was burning in 36 (43.9%) of the total patients with chest pain. Non-respiratory symptoms were seen frequently in acute asthma in ED. Conclusions: Dyspnea was the commonest chest symptoms encountered in patients with acute asthma followed by wheezing. Chest pain in acute asthma is a common symptom and should be fully studied to exclude misdiagnosis as of cardiac origin; there is a need for a better dissemination of knowledge about this disease association with chest pain. It was also noted that other non-respiratory symptoms are frequently encountered with acute asthma in emergency department. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asthma" title="asthma">asthma</a>, <a href="https://publications.waset.org/abstracts/search?q=emergency%20department" title=" emergency department"> emergency department</a>, <a href="https://publications.waset.org/abstracts/search?q=respiratory%20symptoms" title=" respiratory symptoms"> respiratory symptoms</a>, <a href="https://publications.waset.org/abstracts/search?q=non%20respiratory%20system" title=" non respiratory system "> non respiratory system </a> </p> <a href="https://publications.waset.org/abstracts/23631/acute-asthma-in-emergency-department-prevalence-of-respiratory-and-non-respiratory-symptoms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23631.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">425</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">28021</span> Artificial Intelligence-Based Chest X-Ray Test of COVID-19 Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dhurgham%20Al-Karawi">Dhurgham Al-Karawi</a>, <a href="https://publications.waset.org/abstracts/search?q=Nisreen%20Polus"> Nisreen Polus</a>, <a href="https://publications.waset.org/abstracts/search?q=Shakir%20Al-Zaidi"> Shakir Al-Zaidi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sabah%20Jassim"> Sabah Jassim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment. <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=chest%20x-ray%20scan" title=" chest x-ray scan"> chest x-ray scan</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=texture%20analysis" title=" texture analysis"> texture analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20binary%20pattern%20transform" title=" local binary pattern transform"> local binary pattern transform</a>, <a href="https://publications.waset.org/abstracts/search?q=Gabor%20filter" title=" Gabor filter"> Gabor filter</a> </p> <a href="https://publications.waset.org/abstracts/128235/artificial-intelligence-based-chest-x-ray-test-of-covid-19-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128235.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">145</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">28020</span> Efficacy and User Satisfaction on the Rama-Chest Cryo Arm Innovation for Bronchoscopic Cryotherapy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chariya%20Laohavich">Chariya Laohavich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> At the current, the trends in the lung disease at a university hospital are the treat and diagnosis by bronchoscopy. Bronchoscopic cryotherapy is a long time procedure 1-4 hours. The cryo probe is sensitive and easy to be damaged and expensive. We have this study management for protection the cryo probe, user satisfaction and qualities work. This study conducted in 4 stages: stage 1 for a survey of problems and assessment of user’s needs; stage 2 for designing and developing the Rama-chest cryo arm for a bronchoscopy process; stage 3 for test-implementing the Rama-chest cryo arm in real situations, studying its problems and obstacles, and evaluating the user satisfaction; and stage 4 for an overall assessment and improvement. The sample used in this study consisted of a total of 15 Ramathipbodi Hospital’s Bronchoscopist and bronchoscopist’s nurse who had used the Rama-chest cryo arm for bronchoscopic cryotherapy from January to June 2016. Objective: To study efficacy and user satisfaction on the Rama-chest cryo arm innovation for bronchoscopic cryotherapy. Data were collected using a Rama-chest cryo arm satisfaction assessment form and analysed based on mean and standard deviation. Result is the Rama-chest cryo arm was an innovation that accommodated during bronchoscopic cryotherapy. The subjects rated this the cryo arm as being most satisfactory (M = 4.86 ± , SD 0.48. Therefore we have developed a cryo arm that uses local material, practical and economic. Our innovation is not only flexible and sustainable development but also lean and seamless. This produced device can be used as effectively as the imported one, and thus can be eventually substituted. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=efficacy" title="efficacy">efficacy</a>, <a href="https://publications.waset.org/abstracts/search?q=satisfaction" title=" satisfaction"> satisfaction</a>, <a href="https://publications.waset.org/abstracts/search?q=Rama-chest%20cryo%20arm" title=" Rama-chest cryo arm"> Rama-chest cryo arm</a>, <a href="https://publications.waset.org/abstracts/search?q=innovation" title=" innovation"> innovation</a>, <a href="https://publications.waset.org/abstracts/search?q=bronchoscopic%20cryotherapy" title=" bronchoscopic cryotherapy"> bronchoscopic cryotherapy</a> </p> <a href="https://publications.waset.org/abstracts/62116/efficacy-and-user-satisfaction-on-the-rama-chest-cryo-arm-innovation-for-bronchoscopic-cryotherapy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62116.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">243</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">28019</span> Comprehensive Evaluation of COVID-19 Through Chest Images</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> The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance. <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=COVID-19" title=" COVID-19"> COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20Image" title=" chest Image"> chest Image</a>, <a href="https://publications.waset.org/abstracts/search?q=coronavirus" title=" coronavirus"> coronavirus</a>, <a href="https://publications.waset.org/abstracts/search?q=CT%20image" title=" CT image"> CT image</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20CT" title=" chest CT"> chest CT</a> </p> <a href="https://publications.waset.org/abstracts/177502/comprehensive-evaluation-of-covid-19-through-chest-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/177502.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">57</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">28018</span> Comparison of Chest Weight of Pure and Mixed Races Kabood 30-Day Squab</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sepehr%20Moradi">Sepehr Moradi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Asadi%20Rad"> Mehdi Asadi Rad </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study is to evaluate and compare chest weight of pure and mixed races Kabood 30-day Pigeons to investigate about their sex, race, and some auxiliary variables. In this paper, 62 pieces of pigeons as 31 male and female pairs with equal age are studied randomly. A natural incubation was done from each pair. All produced chickens were slaughtered at 30 days age after 12 hours hunger. Then their chests were weighted by a scale with one gram precision. A covariance analysis was used since there were many auxiliary variables and unequal observations. SAS software was used for statistical analysis. Mean weight of chests in pure race (Kabood-Kabood) with 8 records, 123.8±32.3g and mixed races of Kabood-Namebar, Kabood-Parvazy, Kabood-Tizpar, Namebar-Kabood, Tizpar-Kabood, and Parvazi-Kabood with 8, 8, 6, 12, 10, and 10 records were 139.4±23.5, 7/122±23.8, 124.7±30.1, 50.3±29.3, 51.4±26.4, and 137±28.6 gr, respectively. Mean weight of 30-day chests in male and female sex were 87.3±2.5 and 82.7±2.6g, respectively. Difference chest weight of 30-day chests of Kabood-Kabood race with Kabood-Namebar, Kabood-Parvazi, Tizpar-Kabood, Kabood-Tizpar, Namebar-Kabood and Parvazi-Kabood mixed races was not significant. Effect of sex was also significant in 5% level (P<0.05), but mutual effect of sex and race was not significant. Auxiliary variable of father weight was significant in 1% level (p < 0.01), but auxiliary variable of mother weight was not significant. The results showed that most and least weights belonged to Kabood-Namebar and Namebar-Kabood. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=squab" title="squab">squab</a>, <a href="https://publications.waset.org/abstracts/search?q=Kabood%20race" title=" Kabood race"> Kabood race</a>, <a href="https://publications.waset.org/abstracts/search?q=30-day%20chest%20weight" title=" 30-day chest weight"> 30-day chest weight</a>, <a href="https://publications.waset.org/abstracts/search?q=pigeons" title=" pigeons "> pigeons </a> </p> <a href="https://publications.waset.org/abstracts/82666/comparison-of-chest-weight-of-pure-and-mixed-races-kabood-30-day-squab" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82666.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">152</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">28017</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">28016</span> The Usefulness and Limitations of Manual Aspiration Immediately after Pneumothorax Complicating Percutaneous CT Guided Lung Biopsies: A Retrospective 9-Year Review from a Large Tertiary Centre</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Niall%20Fennessy">Niall Fennessy</a>, <a href="https://publications.waset.org/abstracts/search?q=Charlotte%20Yin"> Charlotte Yin</a>, <a href="https://publications.waset.org/abstracts/search?q=Vineet%20Gorolay"> Vineet Gorolay</a>, <a href="https://publications.waset.org/abstracts/search?q=Michael%20Chan"> Michael Chan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilias%20Drivas"> Ilias Drivas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: The aim of this study was to evaluate the effect of manual aspiration of air from the pleural cavity in mitigating the need for chest drain placement after a CT-guided lung biopsy. Method: This is a single institution retrospective review of CT-guided lung biopsies performed on 799 patients between September 2013 and May 2021 in a major tertiary hospital. Percutaneous manual aspiration of air was performed in 104/306 patients (34%) with pneumothoraxes as a preventative measure. Simple and multivariate analysis was performed to identify independent risk factors (modifiable and nonmodifiable) for the success of manual aspiration in mitigating the need for chest drain insertion. Results: The overall incidence of pneumothorax was 37% (295/799). Chest drains were inserted for 81/295 (27%) of the pneumothoraxes, representing 81/799 (10%) of all CT-guided lung biopsies. Of patients with pneumothoraces, 104 (36%) underwent percutaneous aspiration via either the coaxial guide needle or an 18 or 20G intravenous catheter attached to a three-way stopcock and syringe. Amongst this group, 13 patients (13%) subsequently required chest drain insertion. The success of percutaneous aspiration in avoiding subsequent pleural drain insertion decreased with aspiration volume >500mL, radial pneumothorax depth >3cm, increased subpleural depth of the lesion, and the presence of background emphysema. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computed%20tomography" title="computed tomography">computed tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=lung%20biopsy" title=" lung biopsy"> lung biopsy</a>, <a href="https://publications.waset.org/abstracts/search?q=pneumothorax" title=" pneumothorax"> pneumothorax</a>, <a href="https://publications.waset.org/abstracts/search?q=manual%20aspiration" title=" manual aspiration"> manual aspiration</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20drainage" title=" chest drainage"> chest drainage</a> </p> <a href="https://publications.waset.org/abstracts/140907/the-usefulness-and-limitations-of-manual-aspiration-immediately-after-pneumothorax-complicating-percutaneous-ct-guided-lung-biopsies-a-retrospective-9-year-review-from-a-large-tertiary-centre" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140907.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">175</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">28015</span> Traumatic Brachiocephalic Artery Pseudoaneurysm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sally%20Shepherd">Sally Shepherd</a>, <a href="https://publications.waset.org/abstracts/search?q=Jessica%20Wong"> Jessica Wong</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Read"> David Read</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traumatic brachiocephalic artery aneurysm is a rare injury that typically occurs as a result of a blunt chest injury. A 19-year-old female sustained a head-on, high speed motor vehicle crash into a tree. Upon release after 45 minutes of entrapment, she was tachycardic but normotensive, with a significant seatbelt sign across her chest and open deformed right thigh with weak pulses in bilateral lower limbs. A chest XR showed mild upper mediastinal widening. A CT trauma series plus gated CT chest revealed a grade 3a aortic arch transection with brachiocephalic pseudoaneurysm. Endovascular repair of the brachiocephalic artery was attempted post-presentation but was unsuccessful as the first stent migrated to the infrarenal abdominal aorta and the second stent across the brachiocephalic artery origin had a persistent leak at the base. She was transferred to Intensive Care for strict blood pressure control. She returned to theatre 5 hours later for a median sternotomy, aortic arch repair with an 8mm graft extraction, and excision of the innominate artery pseudoaneurysm. She had an uncomplicated post-operative recovery. This case highlights that brachiocephalic artery injury is a rare but potentially lethal injury as a result of blunt chest trauma. Safe management requires a combined Vascular and Cardiothoracic team approach, as stenting alone may be insufficient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blunt%20chest%20injury" title="blunt chest injury">blunt chest injury</a>, <a href="https://publications.waset.org/abstracts/search?q=Brachiocephalic%20aneurysm" title=" Brachiocephalic aneurysm"> Brachiocephalic aneurysm</a>, <a href="https://publications.waset.org/abstracts/search?q=innominate%20artery" title=" innominate artery"> innominate artery</a>, <a href="https://publications.waset.org/abstracts/search?q=trauma" title=" trauma"> trauma</a> </p> <a href="https://publications.waset.org/abstracts/132011/traumatic-brachiocephalic-artery-pseudoaneurysm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132011.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">230</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">28014</span> Comparison of the Chest X-Ray and Computerized Tomography Scans Requested from the Emergency Department</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sahabettin%20Mete">Sahabettin Mete</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20C.%20Hocagil"> Abdullah C. Hocagil</a>, <a href="https://publications.waset.org/abstracts/search?q=Hilal%20Hocagil"> Hilal Hocagil</a>, <a href="https://publications.waset.org/abstracts/search?q=Volkan%20Ulker"> Volkan Ulker</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20C.%20Taskin"> Hasan C. Taskin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objectives and Goals: An emergency department is a place where people can come for a multitude of reasons 24 hours a day. As it is an easy, accessible place, thanks to self-sacrificing people who work in emergency departments. But the workload and overcrowding of emergency departments are increasing day by day. Under these circumstances, it is important to choose a quick, easily accessible and effective test for diagnosis. This results in laboratory and imaging tests being more than 40% of all emergency department costs. Despite all of the technological advances in imaging methods and available computerized tomography (CT), chest X-ray, the older imaging method, has not lost its appeal and effectiveness for nearly all emergency physicians. Progress in imaging methods are very convenient, but physicians should consider the radiation dose, cost, and effectiveness, as well as imaging methods to be carefully selected and used. The aim of the study was to investigate the effectiveness of chest X-ray in immediate diagnosis against the advancing technology by comparing chest X-ray and chest CT scan results of the patients in the emergency department. Methods: Patients who applied to Bulent Ecevit University Faculty of Medicine’s emergency department were investigated retrospectively in between 1 September 2014 and 28 February 2015. Data were obtained via MIAMED (Clear Canvas Image Server v6.2, Toronto, Canada), information management system which patients’ files are saved electronically in the clinic, and were retrospectively scanned. The study included 199 patients who were 18 or older, had both chest X-ray and chest CT imaging. Chest X-ray images were evaluated by the emergency medicine senior assistant in the emergency department, and the findings were saved to the study form. CT findings were obtained from already reported data by radiology department in the clinic. Chest X-ray was evaluated with seven questions in terms of technique and dose adequacy. Patients’ age, gender, application complaints, comorbid diseases, vital signs, physical examination findings, diagnosis, chest X-ray findings and chest CT findings were evaluated. Data saved and statistical analyses have made via using SPSS 19.0 for Windows. And the value of p < 0.05 were accepted statistically significant. Results: 199 patients were included in the study. In 38,2% (n=76) of all patients were diagnosed with pneumonia and it was the most common diagnosis. The chest X-ray imaging technique was appropriate in patients with the rate of 31% (n=62) of all patients. There was not any statistically significant difference (p > 0.05) between both imaging methods (chest X-ray and chest CT) in terms of determining the rates of displacement of the trachea, pneumothorax, parenchymal consolidation, increased cardiothoracic ratio, lymphadenopathy, diaphragmatic hernia, free air levels in the abdomen (in sections including the image), pleural thickening, parenchymal cyst, parenchymal mass, parenchymal cavity, parenchymal atelectasis and bone fractures. Conclusions: When imaging findings, showing cases that needed to be quickly diagnosed, were investigated, chest X-ray and chest CT findings were matched at a high rate in patients with an appropriate imaging technique. However, chest X-rays, evaluated in the emergency department, were frequently taken with an inappropriate technique. <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=chest%20computerized%20tomography" title=" chest computerized tomography"> chest computerized tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20imaging" title=" chest imaging"> chest imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=emergency%20department" title=" emergency department"> emergency department</a> </p> <a href="https://publications.waset.org/abstracts/86937/comparison-of-the-chest-x-ray-and-computerized-tomography-scans-requested-from-the-emergency-department" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/86937.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">192</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">28013</span> Characterization of Chest Pain in Patients Consulting to the Emergency Department of a Health Institution High Level of Complexity during 2014-2015, Medellin, Colombia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jorge%20Iv%C3%A1n%20Ba%C3%B1ol-Betancur">Jorge Iván Bañol-Betancur</a>, <a href="https://publications.waset.org/abstracts/search?q=Lina%20Mar%C3%ADa%20Mart%C3%ADnez-S%C3%A1nchez"> Lina María Martínez-Sánchez</a>, <a href="https://publications.waset.org/abstracts/search?q=Mar%C3%ADa%20de%20los%20%C3%81ngeles%20Rodr%C3%ADguez-G%C3%A1zquez"> María de los Ángeles Rodríguez-Gázquez</a>, <a href="https://publications.waset.org/abstracts/search?q=Estefan%C3%ADa%20Bahamonde-Olaya"> Estefanía Bahamonde-Olaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Ana%20Mar%C3%ADa%20Guti%C3%A9rrez-Tamayo"> Ana María Gutiérrez-Tamayo</a>, <a href="https://publications.waset.org/abstracts/search?q=Laura%20Isabel%20Jaramillo-Jaramillo"> Laura Isabel Jaramillo-Jaramillo</a>, <a href="https://publications.waset.org/abstracts/search?q=Camilo%20Ruiz-Mej%C3%ADa"> Camilo Ruiz-Mejía</a>, <a href="https://publications.waset.org/abstracts/search?q=Natalia%20Morales-Quintero"> Natalia Morales-Quintero</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Acute chest pain is a distressing sensation between the diaphragm and the base of the neck and it represents a diagnostic challenge for any physician in the emergency department. Objective: To establish the main clinical and epidemiological characteristics of patients who present with chest pain to the emergency department in a private clinic from the city of Medellin, during 2014-2015. Methods: Cross-sectional retrospective observational study. Population and sample were patients who consulted for chest pain in the emergency department who met the eligibility criteria. The information was analyzed in SPSS program vr.21; qualitative variables were described through relative frequencies, and the quantitative through mean and standard deviation ‬or medians according to their distribution in the study population. Results: A total of 231 patients were evaluated, the mean age was 49.5 ± 19.9 years, 56.7% were females. The most frequent pathological antecedents were hypertension 35.5%, diabetes 10,8%, dyslipidemia 10.4% and coronary disease 5.2%. Regarding pain features, in 40.3% of the patients the pain began abruptly, in 38.2% it had a precordial location, for 20% of the cases physical activity acted as a trigger, and 60.6% was oppressive. Costochondritis was the most common cause of chest pain among patients with an established etiologic diagnosis, representing the 18.2%. Conclusions: Although the clinical features of pain reported coincide with the clinical presentation of an acute coronary syndrome, the most common cause of chest pain in study population was costochondritis instead, indicating that it is a differential diagnostic in the approach of patients with pain acute chest. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acute%20coronary%20syndrome" title="acute coronary syndrome">acute coronary syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20pain" title=" chest pain"> chest pain</a>, <a href="https://publications.waset.org/abstracts/search?q=epidemiology" title=" epidemiology"> epidemiology</a>, <a href="https://publications.waset.org/abstracts/search?q=osteochondritis" title=" osteochondritis"> osteochondritis</a> </p> <a href="https://publications.waset.org/abstracts/71857/characterization-of-chest-pain-in-patients-consulting-to-the-emergency-department-of-a-health-institution-high-level-of-complexity-during-2014-2015-medellin-colombia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71857.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">343</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">28012</span> Domain-Specific Deep Neural Network Model for Classification of Abnormalities on Chest Radiographs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nkechinyere%20Joy%20Olawuyi">Nkechinyere Joy Olawuyi</a>, <a href="https://publications.waset.org/abstracts/search?q=Babajide%20Samuel%20Afolabi"> Babajide Samuel Afolabi</a>, <a href="https://publications.waset.org/abstracts/search?q=Bola%20Ibitoye"> Bola Ibitoye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent. <p class="card-text"><strong>Keywords:</strong> <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=convolutional%20neural%20network" title=" convolutional neural network"> convolutional neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=radiograph" title=" radiograph"> radiograph</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-label" title=" multi-label"> multi-label</a> </p> <a href="https://publications.waset.org/abstracts/160741/domain-specific-deep-neural-network-model-for-classification-of-abnormalities-on-chest-radiographs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160741.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">129</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">28011</span> A Pilot Study of Influences of Scan Speed on Image Quality for Digital Tomosynthesis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li-Ting%20Huang">Li-Ting Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Hsiang%20Shen"> Yu-Hsiang Shen</a>, <a href="https://publications.waset.org/abstracts/search?q=Cing-Ciao%20Ke"> Cing-Ciao Ke</a>, <a href="https://publications.waset.org/abstracts/search?q=Sheng-Pin%20Tseng"> Sheng-Pin Tseng</a>, <a href="https://publications.waset.org/abstracts/search?q=Fan-Pin%20Tseng"> Fan-Pin Tseng</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Ching%20Ni"> Yu-Ching Ni</a>, <a href="https://publications.waset.org/abstracts/search?q=Chia-Yu%20Lin"> Chia-Yu Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Chest radiography is the most common technique for the diagnosis and follow-up of pulmonary diseases. However, the lesions superimposed with normal structures are difficult to be detected in chest radiography. Chest tomosynthesis is a relatively new technique to obtain 3D section images from a set of low-dose projections acquired over a limited angular range. However, there are some limitations with chest tomosynthesis. Patients undergoing tomosynthesis have to be able to hold their breath firmly for 10 seconds. A digital tomosynthesis system with advanced reconstruction algorithm and high-stability motion mechanism was developed by our research group. The potential for the system to perform a bidirectional chest scan within 10 seconds is expected. The purpose of this study is to realize the influences of the scan speed on the image quality for our digital tomosynthesis system. The major factors that lead image blurring are the motion of the X-ray source and the patient. For the fore one, an experiment of imaging a chest phantom with three different scan speeds, which are 6 cm/s, 8 cm/s, and 15 cm/s, was proceeded to understand the scan speed influences on the image quality. For the rear factor, a normal SD (Sprague-Dawley) rat was imaged with it alive and sacrificed to assess the impact on the image quality due to breath motion. In both experiments, the profile of the ROIs (region of interest) and the CNRs (contrast-to-noise ratio) of the ROIs to the normal tissue of the reconstructed images was examined to realize the degradations of the qualities of the images. The preliminary results show that no obvious degradation of the image quality was observed with increasing scan speed, possibly due to the advanced designs for the hardware and software of the system. It implies that higher speed (15 cm/s) than that of the commercialized tomosynthesis system (12 cm/s) for the proposed system is achieved, and therefore a complete chest scan within 10 seconds is expected. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chest%20radiography" title="chest radiography">chest radiography</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20tomosynthesis" title=" digital tomosynthesis"> digital tomosynthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20quality" title=" image quality"> image quality</a>, <a href="https://publications.waset.org/abstracts/search?q=scan%20speed" title=" scan speed"> scan speed</a> </p> <a href="https://publications.waset.org/abstracts/50916/a-pilot-study-of-influences-of-scan-speed-on-image-quality-for-digital-tomosynthesis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50916.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">331</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">28010</span> Cardiopulmonary Resuscitation Performance Efficacy While Wearing a Powered Air-Purifying Respirator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jun%20Young%20Chong">Jun Young Chong</a>, <a href="https://publications.waset.org/abstracts/search?q=Seung%20Whan%20Kim"> Seung Whan Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: The use of personal protective equipment for respiratory infection control in cardiopulmonary resuscitation (CPR) is a physical burden to healthcare providers. It matters how long CPR quality according to recommended guidelines can be maintained under these circumstances. It was investigated whether chest compression time was appropriate for a 2-minute shift and how long it was maintained in accordance with the guidelines under such conditions. Methods: This prospective crossover simulation study was performed at a single center from September 2020 to October 2020. Five indicators of CPR quality were measured during the first and second sessions of the study period. All participants wore a Level D powered air-purifying respirator (PAPR), and the experiment was conducted using a Resusci Anne manikin, which can measure the quality of chest compressions. Each participant conducted two sessions. In session one, 2-minutes of chest compressions followed by a 2-minute rest was repeated twice; in session two, 1-minute of chest compressions followed by a 1-minute rest was repeated four times. Results: All 34 participants completed the study. The deep and sufficient compression rate was 65.9 ± 13.1 mm in the 1-minute shift group and 61.5 ± 30.5 mm in the 2-minute shift group. The mean depth was 52.8 ±4.3 mm in the 1-minute shift group and 51.0 ± 6.1 mm in the 2-minute shift group. In these two values, there was a statistically significant difference between the two sessions. There was no statistically significant difference in the other CPR quality values. Conclusions: It was suggested that the different standard of current 2-minute to 1-minute cycles due to a significant reduction in the quality of chest compression in cases of CPR with PAPR. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cardiopulmonary%20resuscitation" title="cardiopulmonary resuscitation">cardiopulmonary resuscitation</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20compression" title=" chest compression"> chest compression</a>, <a href="https://publications.waset.org/abstracts/search?q=personal%20protective%20equipment" title=" personal protective equipment"> personal protective equipment</a>, <a href="https://publications.waset.org/abstracts/search?q=powered%20air-purifying%20respirator" title=" powered air-purifying respirator"> powered air-purifying respirator</a> </p> <a href="https://publications.waset.org/abstracts/136943/cardiopulmonary-resuscitation-performance-efficacy-while-wearing-a-powered-air-purifying-respirator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/136943.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">114</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">28009</span> Trauma Scores and Outcome Prediction After Chest Trauma</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Abo%20El%20Nasr">Mohamed Abo El Nasr</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Shoeib"> Mohamed Shoeib</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelhamid%20Abdelkhalik"> Abdelhamid Abdelkhalik</a>, <a href="https://publications.waset.org/abstracts/search?q=Amro%20Serag"> Amro Serag</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Early assessment of severity of chest trauma, either blunt or penetrating is of critical importance in prediction of patient outcome. Different trauma scoring systems are widely available and are based on anatomical or physiological parameters to expect patient morbidity or mortality. Up till now, there is no ideal, universally accepted trauma score that could be applied in all trauma centers and is suitable for assessment of severity of chest trauma patients. Aim: Our aim was to compare various trauma scoring systems regarding their predictability of morbidity and mortality in chest trauma patients. Patients and Methods: This study was a prospective study including 400 patients with chest trauma who were managed at Tanta University Emergency Hospital, Egypt during a period of 2 years (March 2014 until March 2016). The patients were divided into 2 groups according to the mode of trauma: blunt or penetrating. The collected data included age, sex, hemodynamic status on admission, intrathoracic injuries, and associated extra-thoracic injuries. The patients outcome including mortality, need of thoracotomy, need for ICU admission, need for mechanical ventilation, length of hospital stay and the development of acute respiratory distress syndrome were also recorded. The relevant data were used to calculate the following trauma scores: 1. Anatomical scores including abbreviated injury scale (AIS), Injury severity score (ISS), New injury severity score (NISS) and Chest wall injury scale (CWIS). 2. Physiological scores including revised trauma score (RTS), Acute physiology and chronic health evaluation II (APACHE II) score. 3. Combined score including Trauma and injury severity score (TRISS ) and 4. Chest-Specific score Thoracic trauma severity score (TTSS). All these scores were analyzed statistically to detect their sensitivity, specificity and compared regarding their predictive power of mortality and morbidity in blunt and penetrating chest trauma patients. Results: The incidence of mortality was 3.75% (15/400). Eleven patients (11/230) died in blunt chest trauma group, while (4/170) patients died in penetrating trauma group. The mortality rate increased more than three folds to reach 13% (13/100) in patients with severe chest trauma (ISS of >16). The physiological scores APACHE II and RTS had the highest predictive value for mortality in both blunt and penetrating chest injuries. The physiological score APACHE II followed by the combined score TRISS were more predictive for intensive care admission in penetrating injuries while RTS was more predictive in blunt trauma. Also, RTS had a higher predictive value for expectation of need for mechanical ventilation followed by the combined score TRISS. APACHE II score was more predictive for the need of thoracotomy in penetrating injuries and the Chest-Specific score TTSS was higher in blunt injuries. The anatomical score ISS and TTSS score were more predictive for prolonged hospital stay in penetrating and blunt injuries respectively. Conclusion: Trauma scores including physiological parameters have a higher predictive power for mortality in both blunt and penetrating chest trauma. They are more suitable for assessment of injury severity and prediction of patients outcome. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chest%20trauma" title="chest trauma">chest trauma</a>, <a href="https://publications.waset.org/abstracts/search?q=trauma%20scores" title=" trauma scores"> trauma scores</a>, <a href="https://publications.waset.org/abstracts/search?q=blunt%20injuries" title=" blunt injuries"> blunt injuries</a>, <a href="https://publications.waset.org/abstracts/search?q=penetrating%20injuries" title=" penetrating injuries"> penetrating injuries</a> </p> <a href="https://publications.waset.org/abstracts/56701/trauma-scores-and-outcome-prediction-after-chest-trauma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56701.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">421</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">28008</span> Low-Dose Chest Computed Tomography Can Help in Differential Diagnosis of Asthma–COPD Overlap Syndrome in Children</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Frantisek%20Kopriva">Frantisek Kopriva</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamila%20Michalkova"> Kamila Michalkova</a>, <a href="https://publications.waset.org/abstracts/search?q=Radim%20Dudek"> Radim Dudek</a>, <a href="https://publications.waset.org/abstracts/search?q=Jana%20Volejnikova"> Jana Volejnikova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Rationale: Diagnostic criteria of asthma–COPD overlap syndrome (ACOS) are controversial in pediatrics. Emphysema is characteristic of COPD and usually does not occur in typical asthma; its presence in patients with asthma suggests the concurrence with COPD. Low-dose chest computed tomography (CT) allows a non-invasive assessment of the lung tissue structure. Here we present CT findings of emphysematous changes in a child with ACOS. Patient and Methods: In a 6-year-old boy, atopy was confirmed by a skin prick test using common allergen extracts (grass and tree pollen, house dust mite, molds, cat, dog; manufacturer Stallergenes Greer, London, UK), where reactions over 3 mm were considered positive. Treatment with corticosteroids was started during the course of severe asthma. At 12 years of age, his spirometric parameters deteriorated despite treatment adjustment (VC 1.76 L=85%, FEV1 1.13 L=67%, TI%VCmax 64%, MEF25 19%, TLC 144%) and the bronchodilator test became negative. Results: Low-dose chest CT displayed irregular regions with increased radiolucency of pulmonary parenchyma (typical for hyperinflation in emphysematous changes) in both lungs. This was in accordance with the results of spirometric examination. Conclusions: ACOS is infrequent in children. However, low-dose chest CT scan can be considered to confirm this diagnosis or eliminate other diagnoses when the clinical condition is deteriorating and treatment response is poor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=child" title="child">child</a>, <a href="https://publications.waset.org/abstracts/search?q=asthma" title=" asthma"> asthma</a>, <a href="https://publications.waset.org/abstracts/search?q=low-dose%20chest%20CT" title=" low-dose chest CT"> low-dose chest CT</a>, <a href="https://publications.waset.org/abstracts/search?q=ACOS" title=" ACOS"> ACOS</a> </p> <a href="https://publications.waset.org/abstracts/102811/low-dose-chest-computed-tomography-can-help-in-differential-diagnosis-of-asthma-copd-overlap-syndrome-in-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102811.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">146</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">28007</span> Classification of Digital Chest Radiographs Using Image Processing Techniques to Aid in Diagnosis of Pulmonary Tuberculosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20J.%20S.%20P.%20Nileema">A. J. S. P. Nileema</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Kulatunga"> S. Kulatunga </a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Palihawadana"> S. H. Palihawadana </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chest%20radiographs" title="chest radiographs">chest radiographs</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20aided%20detection" title=" computer aided detection"> computer aided detection</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=pulmonary%20tuberculosis" title=" pulmonary tuberculosis"> pulmonary tuberculosis</a> </p> <a href="https://publications.waset.org/abstracts/132114/classification-of-digital-chest-radiographs-using-image-processing-techniques-to-aid-in-diagnosis-of-pulmonary-tuberculosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132114.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">126</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">28006</span> U-Net Based Multi-Output Network for Lung Disease Segmentation and Classification Using Chest X-Ray Dataset</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jaiden%20X.%20Schraut">Jaiden X. Schraut</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database. <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=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20segmentation" title=" image segmentation"> image segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20classification" title=" image classification"> image classification</a> </p> <a href="https://publications.waset.org/abstracts/155537/u-net-based-multi-output-network-for-lung-disease-segmentation-and-classification-using-chest-x-ray-dataset" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155537.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">144</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">28005</span> Epicardial Fat Necrosis in a Young Female: A Case Report</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tayyibah%20Shah%20Alam">Tayyibah Shah Alam</a>, <a href="https://publications.waset.org/abstracts/search?q=Joe%20Thomas"> Joe Thomas</a>, <a href="https://publications.waset.org/abstracts/search?q=Nayantara%20Shenoy"> Nayantara Shenoy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Presenting a case that we would like to share, the answer is straight forward but the path taken to get to the diagnosis is where it gets interesting. A 31-year-old lady presented to the Rheumatology Outpatient department with left-sided chest pain associated with left-sided elbow joint pain intensifying over the last 2 days. She had been having a prolonged history of chest pain with minimal intensity since 2016. The pain is intermittent in nature. Aggravated while exerting, lifting heavy weights and lying down. Relieved while sitting. Her physical examination and laboratory tests were within normal limits. An electrocardiogram (ECG) showed normal sinus rhythm and a chest X-ray with no significant abnormality was noted. The primary suspicion was recurrent costochondritis. Cardiac blood inflammatory markers and Echo were normal, ruling out ACS. CT chest and MRI Thorax contrast showed small ill-defined STIR hyperintensity with thin peripheral enhancement in the anterior mediastinum in the left side posterior to the 5th costal cartilage and anterior to the pericardium suggestive of changes in the fat-focal panniculitis. Confirming the diagnosis as Epicardial fat necrosis. She was started on Colchicine and Nonsteroidal anti-inflammatory drugs for 2-3 weeks, following which a repeat CT showed resolution of the lesion and improvement in her. It is often under-recognized or misdiagnosed. CT scan was collectively used to establish the diagnosis. Making the correct diagnosis prospectively alleviates unnecessary testing in favor of conservative management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EFN" title="EFN">EFN</a>, <a href="https://publications.waset.org/abstracts/search?q=panniculitis" title=" panniculitis"> panniculitis</a>, <a href="https://publications.waset.org/abstracts/search?q=unknown%20etiology" title=" unknown etiology"> unknown etiology</a>, <a href="https://publications.waset.org/abstracts/search?q=recurrent%20chest%20pain" title=" recurrent chest pain"> recurrent chest pain</a> </p> <a href="https://publications.waset.org/abstracts/152354/epicardial-fat-necrosis-in-a-young-female-a-case-report" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152354.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">97</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">28004</span> Asymptomatic Intercostal Schwannoma in a Patient with COVID-19: The First of Its Kind</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gabriel%20Hunduma">Gabriel Hunduma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Asymptomatic intra-thoracic neurogenic tumours are rare. Tumours arising from the intercostal nerves of the chest wall are exceedingly rare. This paper reports an incidental discovery of a neurogenic intercostal tumour while being investigated for Coronavirus Disease 2019 (COVID-19). A 54-year-old female underwent a thoracotomy and resection for an intercostal tumour. Pre-operative images showed an intrathoracic mass, and the biopsy revealed a schwannoma. The most common presenting symptom recorded in literature is chest pain; however, our case remained asymptomatic despite the size of the mass and thoracic area it occupied. After an extensive search of the literature, COVID-19 was found to have an influence on the development of certain cells in breast cancer. Hence there is a possibility that COVID-19 played a role in progressing the development of the schwannoma cells. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thoracic%20surgery" title="thoracic surgery">thoracic surgery</a>, <a href="https://publications.waset.org/abstracts/search?q=intercostal%20schwannoma" title=" intercostal schwannoma"> intercostal schwannoma</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20wall%20oncology" title=" chest wall oncology"> chest wall oncology</a>, <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title=" COVID-19"> COVID-19</a> </p> <a href="https://publications.waset.org/abstracts/140781/asymptomatic-intercostal-schwannoma-in-a-patient-with-covid-19-the-first-of-its-kind" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140781.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">214</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">28003</span> Hemodynamic Effects of Magnesium Sulphate Therapy in Critically Ill Infants and Children with Wheezy Chest </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yasmin%20Sayed">Yasmin Sayed</a>, <a href="https://publications.waset.org/abstracts/search?q=Hala%20Hamdy"> Hala Hamdy</a>, <a href="https://publications.waset.org/abstracts/search?q=Hafez%20Bazaraa"> Hafez Bazaraa</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanaa%20Rady"> Hanaa Rady</a>, <a href="https://publications.waset.org/abstracts/search?q=Sherif%20Elanwary"> Sherif Elanwary</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intravenous and inhaled magnesium sulfate (MgSO₄) had been recently used as an adjuvant therapy in cases suffering from the wheezy chest. Objective: We aimed to determine the possible change in the hemodynamic state in cases received intravenous or inhaled MgSO₄ in comparison to cases received standard treatment in critically ill infants and children with the wheezy chest. Methods: A randomized controlled trial comprised 81 patients suffering from wheezy chest divided into 3 groups. In addition to bronchodilators and systemic steroids, MgSO₄ was given by inhalation in group A, intravenously in group B, and group C didn't receive MgSO₄. The hemodynamic state was determined by assessment of blood pressure, heart rate, capillary refill time and the need for shock therapy or inotropic support just before and 24 hours after receiving treatment in 3 groups. Results: There was no significant difference in the hemodynamic state of the studied groups before and after treatment. Means of blood pressure were 102.2/63.2, 105.1/64.8 before and after inhaled MgSO₄; respectively. Means of blood pressure were 105.5/64.2, 104.1/64.9 before and after intravenous MgSO₄; respectively. Means of blood pressure were 107.4/62.8, 104.4/62.1 before and after standard treatment, respectively. There was a statistically insignificant reduction of the means of the heart rate in group A and group B after treatment rather than group C. There was no associated prolongation in capillary refill time and/or the need for inotropic support or shock therapy after treatment in the studied groups. Conclusion: MgSO₄ is a safe adjuvant therapy and not associated with significant alteration in the hemodynamic state in critically ill infants and children with the wheezy chest. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=critically%20ill%20infants%20and%20children" title="critically ill infants and children">critically ill infants and children</a>, <a href="https://publications.waset.org/abstracts/search?q=inhaled%20MgSO%E2%82%84" title=" inhaled MgSO₄"> inhaled MgSO₄</a>, <a href="https://publications.waset.org/abstracts/search?q=intravenous%20MgSO%E2%82%84" title=" intravenous MgSO₄"> intravenous MgSO₄</a>, <a href="https://publications.waset.org/abstracts/search?q=wheezy%20chest" title=" wheezy chest"> wheezy chest</a> </p> <a href="https://publications.waset.org/abstracts/92298/hemodynamic-effects-of-magnesium-sulphate-therapy-in-critically-ill-infants-and-children-with-wheezy-chest" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92298.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">148</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">28002</span> A Rare Cause of Abdominal Pain Post Caesarean Section</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Madeleine%20Cox">Madeleine Cox</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: discussion of diagnosis of vernix caseosa peritonitis, recovery and subsequent caesarean seciton Case: 30 year old G4P1 presented in labour at 40 weeks, planning a vaginal birth afterprevious caesarean section. She underwent an emergency caesarean section due to concerns for fetal wellbeing on CTG. She was found to have a thin lower segment with a very small area of dehiscence centrally. The operation was uncomplicated, and she recovered and went home 2 days later. She then represented to the emergency department day 6 post partum feeling very unwell, with significant abdominal pain, tachycardia as well as urinary retention. Raised white cell count of 13.7 with neutrophils of 11.64, CRP of 153. An abdominal ultrasound was poorly tolerated by the patient and did not aide in the diagnosis. Chest and abdominal xray were normal. She underwent a CT chest and abdomen, which found a small volume of free fluid with no apparent collection. Given no obvious cause of her symptoms were found and the patient did not improve, she had a repeat CT 2 days later, which showed progression of free fluid. A diagnostic laparoscopy was performed with general surgeons, which reveled turbid fluid, an inflamed appendix which was removed. The patient improved remarkably post operatively. The histology showed periappendicitis with acute appendicitis with marked serosal inflammatory reaction to vernix caseosa. Following this, the patient went on to recover well. 4 years later, the patient was booked for an elective caesarean section, on entry into the abdomen, there were very minimal adhesions, and the surgery and her subsequent recovery was uncomplicated. Discussion: this case represents the diagnostic dilemma of a patient who presents unwell without a clear cause. In this circumstance, multiple modes of imaging did not aide in her diagnosis, and so she underwent diagnostic surgery. It is important to evaluate if a patient is or is not responding to the typical causes of post operative pain and adjust management accordingly. A multiteam approach can help to provide a diagnosis for these patients. Conclusion: Vernix caseosa peritonitis is a rare cause of acute abdomen post partum. There are few reports in the literature of the initial presentation and no reports on the possible effects on future pregnancies. This patient did not have any complications in her following pregnancy or delivery secondary to her diagnosis of vernix caseosa peritonitis. This may assist in counselling other women who have had this uncommon diagnosis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=peritonitis" title="peritonitis">peritonitis</a>, <a href="https://publications.waset.org/abstracts/search?q=obstetrics" title=" obstetrics"> obstetrics</a>, <a href="https://publications.waset.org/abstracts/search?q=caesarean%20section" title=" caesarean section"> caesarean section</a>, <a href="https://publications.waset.org/abstracts/search?q=pain" title=" pain"> pain</a> </p> <a href="https://publications.waset.org/abstracts/148756/a-rare-cause-of-abdominal-pain-post-caesarean-section" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148756.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">104</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">28001</span> Development of a Practical Screening Measure for the Prediction of Low Birth Weight and Neonatal Mortality in Upper Egypt</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Prof.%20Ammal%20Mokhtar%20Metwally">Prof. Ammal Mokhtar Metwally</a>, <a href="https://publications.waset.org/abstracts/search?q=Samia%20M.%20Sami"> Samia M. Sami</a>, <a href="https://publications.waset.org/abstracts/search?q=Nihad%20A.%20Ibrahim"> Nihad A. Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatma%20A.%20Shaaban"> Fatma A. Shaaban</a>, <a href="https://publications.waset.org/abstracts/search?q=Iman%20I.%20Salama"> Iman I. Salama</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objectives: Reducing neonatal mortality by 2030 is still a challenging goal in developing countries. low birth weight (LBW) is a significant contributor to this, especially where weighing newborns is not possible routinely. The present study aimed to determine a simple, easy, reliable anthropometric measure(s) that can predict LBW) and neonatal mortality. Methods: A prospective cohort study of 570 babies born in districts of El Menia governorate, Egypt (where most deliveries occurred at home) was examined at birth. Newborn weight, length, head, chest, mid-arm, and thigh circumferences were measured. Follow up of the examined neonates took place during their first four weeks of life to report any mortalities. The most predictable anthropometric measures were determined using the statistical package of SPSS, and multiple Logistic regression analysis was performed.: Results: Head and chest circumferences with cut-off points < 33 cm and ≤ 31.5 cm, respectively, were the significant predictors for LBW. They carried the best combination of having the highest sensitivity (89.8 % & 86.4 %) and least false negative predictive value (1.4 % & 1.7 %). Chest circumference with a cut-off point ≤ 31.5 cm was the significant predictor for neonatal mortality with 83.3 % sensitivity and 0.43 % false negative predictive value. Conclusion: Using chest circumference with a cut-off point ≤ 31.5 cm is recommended as a single simple anthropometric measurement for the prediction of both LBW and neonatal mortality. The predicted measure could act as a substitute for weighting newborns in communities where scales to weigh them are not routinely available. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=low%20birth%20weight" title="low birth weight">low birth weight</a>, <a href="https://publications.waset.org/abstracts/search?q=neonatal%20mortality" title=" neonatal mortality"> neonatal mortality</a>, <a href="https://publications.waset.org/abstracts/search?q=anthropometric%20measures" title=" anthropometric measures"> anthropometric measures</a>, <a href="https://publications.waset.org/abstracts/search?q=practical%20screening" title=" practical screening"> practical screening</a> </p> <a href="https://publications.waset.org/abstracts/162775/development-of-a-practical-screening-measure-for-the-prediction-of-low-birth-weight-and-neonatal-mortality-in-upper-egypt" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162775.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">99</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">28000</span> Predictive Analysis of Chest X-rays Using NLP and Large Language Models with the Indiana University Dataset and Random Forest Classifier</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azita%20Ramezani">Azita Ramezani</a>, <a href="https://publications.waset.org/abstracts/search?q=Ghazal%20Mashhadiagha"> Ghazal Mashhadiagha</a>, <a href="https://publications.waset.org/abstracts/search?q=Bahareh%20Sanabakhsh"> Bahareh Sanabakhsh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing%20%28NLP%29" title="natural language processing (NLP)">natural language processing (NLP)</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20language%20models%20%28LLMs%29" title=" large language models (LLMs)"> large language models (LLMs)</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest%20classifier" title=" random forest classifier"> random forest classifier</a>, <a href="https://publications.waset.org/abstracts/search?q=chest%20x-ray%20analysis" title=" chest x-ray analysis"> chest x-ray analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20imaging" title=" medical imaging"> medical imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnostic%20accuracy" title=" diagnostic accuracy"> diagnostic accuracy</a>, <a href="https://publications.waset.org/abstracts/search?q=indiana%20university%20dataset" title=" indiana university dataset"> indiana university dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20in%20healthcare" title=" machine learning in healthcare"> machine learning in healthcare</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20modeling" title=" predictive modeling"> predictive modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support%20systems" title=" clinical decision support systems"> clinical decision support systems</a> </p> <a href="https://publications.waset.org/abstracts/186638/predictive-analysis-of-chest-x-rays-using-nlp-and-large-language-models-with-the-indiana-university-dataset-and-random-forest-classifier" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186638.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">43</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">27999</span> Estimation of Adult Patient Doses for Chest X-Ray Diagnostic Examinations in a Tertiary Institution Health Centre</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20E.%20Okungbowa">G. E. Okungbowa</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20O.%20Adams"> H. O. Adams</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20E.%20Eze"> S. E. Eze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study is on the estimation of adult patient doses for Chest X-ray diagnostic examinations of new admitted undergraduate students attending a tertiary institution health centre as part of their routine clearance and check up on admitted into the institution. A total of 531 newly admitted undergraduate students were recruited for this survey in the first quarter of 2016 (January to March, 2016). CALDOSE_X 5.0 software was used to compute the Entrance Surface Dose (ESD) and Effective Dose (ED); while the Statistical Package for Social Sciences (SPSS) version 21.0 was used to carry out the statistical analyses. The basic patients' data and exposure parameters required for the software are age, sex, examination type, projection posture, tube potential and current-time product. The mean Entrance Surface Dose and Effective Doses of the undergraduate students were calculated using the software, and the values were compared with existing literature and internationally established diagnostic reference levels. The mean ESD calculated is 0.29 mGy, and the mean effective dose is 0.04 mSv. The values of ESD and ED obtained are below the internationally established diagnostic reference levels, which could be attributed to good radiographic techniques employed during the chest X-ray procedure for these students. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=x-ray" title="x-ray">x-ray</a>, <a href="https://publications.waset.org/abstracts/search?q=dose" title=" dose"> dose</a>, <a href="https://publications.waset.org/abstracts/search?q=examination" title=" examination"> examination</a>, <a href="https://publications.waset.org/abstracts/search?q=chest" title=" chest"> chest</a> </p> <a href="https://publications.waset.org/abstracts/65198/estimation-of-adult-patient-doses-for-chest-x-ray-diagnostic-examinations-in-a-tertiary-institution-health-centre" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65198.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span 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