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decision support systems</title> <meta name="description" content="Search results for: clinical decision support systems"> <meta name="keywords" content="clinical decision support systems"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" 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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="clinical decision support systems"> <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> 20872</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: clinical decision support systems</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20872</span> Introducing Design Principles for Clinical Decision Support Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Luca%20Martignoni">Luca Martignoni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The increasing usage of clinical decision support systems in healthcare and the demand for software that enables doctors to take informed decisions is changing everyday clinical practice. However, as technology advances not only are the benefits of technology growing, but so are the potential risks. A growing danger is the doctors’ over-reliance on the proposed decision of the clinical decision support system, leading towards deskilling and rash decisions by doctors. In that regard, identifying doctors' requirements for software and developing approaches to prevent technological over-reliance is of utmost importance. In this paper, we report the results of a design science research study, focusing on the requirements and design principles of ultrasound software. We conducted a total of 15 interviews with experts about poten-tial ultrasound software functions. Subsequently, we developed meta-requirements and design principles to design future clinical decision support systems efficiently and as free from the occur-rence of technological over-reliance as possible. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support%20systems" title="clinical decision support systems">clinical decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=technological%20over-reliance" title=" technological over-reliance"> technological over-reliance</a>, <a href="https://publications.waset.org/abstracts/search?q=design%20principles" title=" design principles"> design principles</a>, <a href="https://publications.waset.org/abstracts/search?q=design%20science%20research" title=" design science research"> design science research</a> </p> <a href="https://publications.waset.org/abstracts/164680/introducing-design-principles-for-clinical-decision-support-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164680.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">100</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">20871</span> A Script for Presentation to the Management of a Teaching Hospital on DXplain Clinical Decision Support System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jacob%20Nortey">Jacob Nortey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. According to the Ibero – American Study of Adverse Effects (IBEAS), about 10% of hospital patients suffer from secondary damage during the care process, and approximately 2% die from this process. Many clinical decision support systems have been developed to help mitigate some healthcare medical errors. Method: Relevant databases were searched, including ones that were peculiar to the clinical decision support system (that is, using google scholar, Pub Med and general google searches). The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of Dxplain Clinical decision support systems. Results: Inferences drawn from the articles showed high usage of Dxplain clinical decision support system for problem-based learning among students in developed countries as against little or no usage among students in Low – and Middle – income Countries. The results also indicated high usage among general practitioners. Conclusion: Despite the challenges Dxplain presents, the benefits of its usage to clinicians and students are enormous. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dxplain" title="dxplain">dxplain</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support%20sytem" title=" clinical decision support sytem"> clinical decision support sytem</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title=" diagnosis"> diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20systems" title=" support systems"> support systems</a> </p> <a href="https://publications.waset.org/abstracts/165029/a-script-for-presentation-to-the-management-of-a-teaching-hospital-on-dxplain-clinical-decision-support-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165029.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">79</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">20870</span> A Script for Presentation to the Management of a Teaching Hospital on MYCIN: A Clinical Decision Support System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashida%20Suleiman">Rashida Suleiman</a>, <a href="https://publications.waset.org/abstracts/search?q=Asamoah%20Jnr.%20Boakye"> Asamoah Jnr. Boakye</a>, <a href="https://publications.waset.org/abstracts/search?q=Suleiman%20Ahmed%20Ibn%20Ahmed"> Suleiman Ahmed Ibn Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. MYCIN is a groundbreaking illustration of a clinical decision support system (CDSS), which was developed to assist physicians in the diagnosis and treatment of bacterial infections by providing suggestions for antibiotic regimens. MYCIN was one of the earliest expert systems to demonstrate how CDSSs may assist human decision-making in complicated areas. Relevant databases were searched using google scholar, PubMed and general Google search, which were peculiar to clinical decision support systems. The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of MYCIN, a clinical decision support system. Inferences drawn from the articles showed some usage of MYCIN for problem-based learning among clinicians and students in some countries. Furthermore, the data demonstrated that MYCIN had completed clinical testing at Stanford University Hospital following years of research. The system (MYCIN) was shown to be extremely accurate and effective in diagnosing and treating bacterial infections, and it demonstrated how CDSSs might enhance clinical decision-making in difficult circumstances. Despite the challenges MYCIN presents, the benefits of its usage to clinicians, students and software developers are enormous. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support%20system" title="clinical decision support system">clinical decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=MYCIN" title=" MYCIN"> MYCIN</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title=" diagnosis"> diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=bacterial%20infections" title=" bacterial infections"> bacterial infections</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20systems" title=" support systems"> support systems</a> </p> <a href="https://publications.waset.org/abstracts/165608/a-script-for-presentation-to-the-management-of-a-teaching-hospital-on-mycin-a-clinical-decision-support-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165608.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">20869</span> Temporal Case-Based Reasoning System for Automatic Parking Complex</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alexander%20P.%20Eremeev">Alexander P. Eremeev</a>, <a href="https://publications.waset.org/abstracts/search?q=Ivan%20E.%20Kurilenko"> Ivan E. Kurilenko</a>, <a href="https://publications.waset.org/abstracts/search?q=Pavel%20R.%20Varshavskiy"> Pavel R. Varshavskiy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analogous%20reasoning" title="analogous reasoning">analogous reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=case-based%20reasoning" title=" case-based reasoning"> case-based reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20decision%20support%20systems" title=" intelligent decision support systems"> intelligent decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal%20reasoning" title=" temporal reasoning"> temporal reasoning</a> </p> <a href="https://publications.waset.org/abstracts/21478/temporal-case-based-reasoning-system-for-automatic-parking-complex" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21478.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">529</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">20868</span> Evaluation of Clinical Decision Support System in Electronic Medical Record System: A Case of Malawi National Art Electronic Medical Record System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pachawo%20Bisani">Pachawo Bisani</a>, <a href="https://publications.waset.org/abstracts/search?q=Goodall%20Nyirenda"> Goodall Nyirenda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Malawi National Antiretroviral Therapy (NART) Electronic Medical Record (EMR) system was designed and developed with guidance from the Ministry of Health through the Department of HIV and AIDS (DHA) with the aim of supporting the management of HIV patient data and reporting in high prevalence ART clinics. As of 2021, the system has been scaled up to over 206 facilities across the country. The system is integrated with the clinical decision support system (CDSS) to assist healthcare providers in making a decision about an individual patient at a particular point in time. Despite NART EMR undergoing several evaluations and assessments, little has been done to evaluate the clinical decision support system in the NART EMR system. Hence, the study aimed to evaluate the use of CDSS in the NART EMR system in Malawi. The study adopted a mixed-method approach, and data was collected through interviews, observations, and questionnaires. The study has revealed that the CDSS tools were integrated into the ART clinic workflow, making it easy for the user to use it. The study has also revealed challenges in system reliability and information accuracy. Despite the challenges, the study further revealed that the system is effective and efficient, and overall, users are satisfied with the system. The study recommends that the implementers focus more on the logic behind the clinical decision-support intervention in order to address some of the concerns and enhance the accuracy of the information supplied. The study further suggests consulting the system's actual users throughout implementation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support%20system" title="clinical decision support system">clinical decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=electronic%20medical%20record%20system" title=" electronic medical record system"> electronic medical record system</a>, <a href="https://publications.waset.org/abstracts/search?q=usability" title=" usability"> usability</a>, <a href="https://publications.waset.org/abstracts/search?q=antiretroviral%20therapy" title=" antiretroviral therapy"> antiretroviral therapy</a> </p> <a href="https://publications.waset.org/abstracts/159450/evaluation-of-clinical-decision-support-system-in-electronic-medical-record-system-a-case-of-malawi-national-art-electronic-medical-record-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159450.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">20867</span> Conceptualizing Thoughtful Intelligence for Sustainable Decision Making</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Musarrat%20Jabeen">Musarrat Jabeen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thoughtful%20intelligence" title="thoughtful intelligence">thoughtful intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable%20decision%20making" title=" sustainable decision making"> sustainable decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=thoughtful%20decision%20support%20system" title=" thoughtful decision support system "> thoughtful decision support system </a> </p> <a href="https://publications.waset.org/abstracts/114747/conceptualizing-thoughtful-intelligence-for-sustainable-decision-making" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/114747.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">135</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">20866</span> Isolation Preserving Medical Conclusion Hold Structure via C5 Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Swati%20Kishor%20Zode">Swati Kishor Zode</a>, <a href="https://publications.waset.org/abstracts/search?q=Rahul%20Ambekar"> Rahul Ambekar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data mining is the extraction of fascinating examples on the other hand information from enormous measure of information and choice is made as indicated by the applicable information extracted. As of late, with the dangerous advancement in internet, stockpiling of information and handling procedures, privacy preservation has been one of the major (higher) concerns in data mining. Various techniques and methods have been produced for protection saving data mining. In the situation of Clinical Decision Support System, the choice is to be made on the premise of the data separated from the remote servers by means of Internet to diagnose the patient. In this paper, the fundamental thought is to build the precision of Decision Support System for multiple diseases for different maladies and in addition protect persistent information while correspondence between Clinician side (Client side) also, the Server side. A privacy preserving protocol for clinical decision support network is proposed so that patients information dependably stay scrambled amid diagnose prepare by looking after the accuracy. To enhance the precision of Decision Support System for various malady C5.0 classifiers and to save security, a Homomorphism encryption algorithm Paillier cryptosystem is being utilized. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=homomorphic%20encryption" title=" homomorphic encryption"> homomorphic encryption</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support" title=" clinical decision support"> clinical decision support</a>, <a href="https://publications.waset.org/abstracts/search?q=privacy" title=" privacy "> privacy </a> </p> <a href="https://publications.waset.org/abstracts/32625/isolation-preserving-medical-conclusion-hold-structure-via-c5-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32625.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">330</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">20865</span> A Multi-criteria Decision Support System for Migrating Legacies into Open Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nasser%20Almonawer">Nasser Almonawer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Timely reaction to an evolving global business environment and volatile market conditions necessitates system and process flexibility, which in turn demands agile and adaptable architecture and a steady infusion of affordable new technologies. On the contrary, a large number of organizations utilize systems characterized by inflexible and obsolete legacy architectures. To effectively respond to the dynamic contemporary business environments, such architectures must be migrated to robust and modular open architectures. To this end, this paper proposes an integrated decision support system for a seamless migration to open systems. The proposed decision support system (DSS) integrates three well-established quantitative and qualitative decision-making models—namely, the Delphi method, Analytic Hierarchy Process (AHP) and Goal Programming (GP) to (1) assess risks and establish evaluation criteria; (2) formulate migration strategy and rank candidate systems; and (3) allocate resources among the selected systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20systems" title="decision support systems">decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20systems%20architecture" title=" open systems architecture"> open systems architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=analytic%20hierarchy%20process%20%28AHP%29" title=" analytic hierarchy process (AHP)"> analytic hierarchy process (AHP)</a>, <a href="https://publications.waset.org/abstracts/search?q=goal%20programming%20%28GP%29" title=" goal programming (GP)"> goal programming (GP)</a>, <a href="https://publications.waset.org/abstracts/search?q=delphi%20method" title=" delphi method"> delphi method</a> </p> <a href="https://publications.waset.org/abstracts/187670/a-multi-criteria-decision-support-system-for-migrating-legacies-into-open-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187670.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">47</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">20864</span> Employing Operations Research at Universities to Build Management Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdallah%20A.%20Hlayel">Abdallah A. Hlayel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Operations research science (OR) deals with good success in developing and applying scientific methods for problem solving and decision-making. However, by using OR techniques, we can enhance the use of computer decision support systems to achieve optimal management for institutions. OR applies comprehensive analysis including all factors that affect on it and builds mathematical modeling to solve business or organizational problems. In addition, it improves decision-making and uses available resources efficiently. The adoption of OR by universities would definitely contributes to the development and enhancement of the performance of OR techniques. This paper provides an understanding of the structures, approaches and models of OR in problem solving and decision-making. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=best%20candidates%27%20method" title="best candidates' method">best candidates' method</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20making" title=" decision making"> decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20system" title=" decision support system"> decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=operations%20research" title=" operations research"> operations research</a> </p> <a href="https://publications.waset.org/abstracts/20107/employing-operations-research-at-universities-to-build-management-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20107.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">445</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">20863</span> Improving Decision Support for Organ Transplant</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ian%20McCulloh">Ian McCulloh</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Placona"> Andrew Placona</a>, <a href="https://publications.waset.org/abstracts/search?q=Darren%20Stewart"> Darren Stewart</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Gause"> Daniel Gause</a>, <a href="https://publications.waset.org/abstracts/search?q=Kevin%20Kiernan"> Kevin Kiernan</a>, <a href="https://publications.waset.org/abstracts/search?q=Morgan%20Stuart"> Morgan Stuart</a>, <a href="https://publications.waset.org/abstracts/search?q=Christopher%20Zinner"> Christopher Zinner</a>, <a href="https://publications.waset.org/abstracts/search?q=Laura%20Cartwright"> Laura Cartwright</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An estimated 22-25% of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. As many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20science" title="decision science">decision science</a>, <a href="https://publications.waset.org/abstracts/search?q=KDPI" title=" KDPI"> KDPI</a>, <a href="https://publications.waset.org/abstracts/search?q=optimism%20bias" title=" optimism bias"> optimism bias</a>, <a href="https://publications.waset.org/abstracts/search?q=organ%20transplant" title=" organ transplant"> organ transplant</a> </p> <a href="https://publications.waset.org/abstracts/160221/improving-decision-support-for-organ-transplant" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160221.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">105</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">20862</span> Decision Support System for Optimal Placement of Wind Turbines in Electric Distribution Grid</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Ouammi">Ahmed Ouammi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an integrated decision framework to support decision makers in the selection and optimal allocation of wind power plants in the electric grid. The developed approach intends to maximize the benefice related to the project investment during the planning period. The proposed decision model considers the main cost components, meteorological data, environmental impacts, operation and regulation constraints, and territorial information. The decision framework is expressed as a stochastic constrained optimization problem with the aim to identify the suitable locations and related optimal wind turbine technology considering the operational constraints and maximizing the benefice. The developed decision support system is applied to a case study to demonstrate and validate its performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20systems" title="decision support systems">decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=electric%20power%20grid" title=" electric power grid"> electric power grid</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title=" wind energy "> wind energy </a> </p> <a href="https://publications.waset.org/abstracts/122208/decision-support-system-for-optimal-placement-of-wind-turbines-in-electric-distribution-grid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/122208.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">153</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">20861</span> Using Visualization Techniques to Support Common Clinical Tasks in Clinical Documentation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jonah%20Kenei">Jonah Kenei</a>, <a href="https://publications.waset.org/abstracts/search?q=Elisha%20Opiyo"> Elisha Opiyo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Electronic health records, as a repository of patient information, is nowadays the most commonly used technology to record, store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by a lack of clear structure. Therefore, medical practice is facing a challenge thanks to the rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient. As a result, there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential for training accurate statistical models to classify facets of information which can then be used to improve patient care and outcomes. However, in many clinical note datasets, the unstructured nature of clinical texts is a common problem. This paper examines the very issue of getting raw clinical texts and mapping them into meaningful structures that can support healthcare professionals utilizing narrative texts. Our work is the result of a collaborative design process that was aided by empirical data collected through formal usability testing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=electronic%20health%20records" title=" electronic health records"> electronic health records</a>, <a href="https://publications.waset.org/abstracts/search?q=narrative%20texts" title=" narrative texts"> narrative texts</a>, <a href="https://publications.waset.org/abstracts/search?q=visualization" title=" visualization"> visualization</a> </p> <a href="https://publications.waset.org/abstracts/148345/using-visualization-techniques-to-support-common-clinical-tasks-in-clinical-documentation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148345.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">118</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">20860</span> Fuzzy Decision Support System for Human-Realistic Overtaking in Railway Traffic Simulations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tom%C3%A1%C5%A1%20Vy%C4%8D%C3%ADtal">Tomáš Vyčítal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In a simulation model of a railway system it is important, besides other crucial algorithms, to have correct behaviour of train overtaking in stochastic conditions. This problem is being addressed in many simulation tools focused on railway traffic, however these are not very human-realistic. The goal of this paper is to create a more human-realistic overtaking decision support system for the use in railway traffic simulations. A fuzzy system has been chosen for this task as fuzzy systems are well-suited for human-like decision making. The fuzzy system designed takes into account timetables, train positions, delays and buffer times as inputs and provides an instruction to overtake or not overtake. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision-making%20support" title="decision-making support">decision-making support</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20systems" title=" fuzzy systems"> fuzzy systems</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=railway" title=" railway"> railway</a>, <a href="https://publications.waset.org/abstracts/search?q=transport" title=" transport"> transport</a> </p> <a href="https://publications.waset.org/abstracts/156626/fuzzy-decision-support-system-for-human-realistic-overtaking-in-railway-traffic-simulations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/156626.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">139</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">20859</span> Decision Support System for a Pilot Flash Flood Early Warning System in Central Chile</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20Pinto">D. Pinto</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Castro"> L. Castro</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20L.%20Cruzat"> M. L. Cruzat</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Barros"> S. Barros</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Giron%C3%A1s"> J. Gironás</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Oberli"> C. Oberli</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Torres"> M. Torres</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Escauriaza"> C. Escauriaza</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Cipriano"> A. Cipriano</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20systems" title="decision support systems">decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=early%20warning%20systems" title=" early warning systems"> early warning systems</a>, <a href="https://publications.waset.org/abstracts/search?q=flash%20flood" title=" flash flood"> flash flood</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20hazard" title=" natural hazard"> natural hazard</a> </p> <a href="https://publications.waset.org/abstracts/26122/decision-support-system-for-a-pilot-flash-flood-early-warning-system-in-central-chile" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26122.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">373</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">20858</span> Service Blueprint for Improving Clinical Guideline Adherence via Mobile Health Technology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Y.%20O%E2%80%99Connor">Y. O’Connor</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Heavin"> C. Heavin</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20O%E2%80%99%20Connor"> S. O’ Connor</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Gallagher"> J. Gallagher</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Wu"> J. Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20O%E2%80%99Donoghue"> J. O’Donoghue</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: To improve the delivery of paediatric healthcare in resource-poor settings, Community Health Workers (CHW) have been provided with a paper-based set of protocols known as Community Case Management (CCM). Yet research has shown that CHW adherence to CCM guidelines is poor, ultimately impacting health service delivery. Digitising the CCM guidelines via mobile technology is argued in extant literature to improve CHW adherence. However, little research exist which outlines how (a) this process can be digitised and (b) adherence could be improved as a result. Aim: To explore how an electronic mobile version of CCM (eCCM) can overcome issues associated with the paper-based CCM protocol (poor adherence to guidelines) vis-à-vis service blueprinting. This service blueprint will outline how (a) the CCM process can be digitised using mobile Clinical Decision Support Systems software to support clinical decision-making and (b) adherence can be improved as a result. Method: Development of a single service blueprint for a standalone application which visually depicts the service processes (eCCM) when supporting the CHWs, using an application known as Supporting LIFE (Low cost Intervention For disEase control) as an exemplar. Results: A service blueprint is developed which illustrates how the eCCM solution can be utilised by CHWs to assist with the delivery of healthcare services to children. Leveraging smartphone technologies can (a) provide CHWs with just-in-time data to assist with their decision making at the point-of-care and (b) improve CHW adherence to CCM guidelines. Conclusions: The development of the eCCM opens up opportunities for the CHWs to leverage the inherent benefit of mobile devices to assist them with health service delivery in rural settings. To ensure that benefits are achieved, it is imperative to comprehend the functionality and form of the eCCM service process. By creating such a service blueprint for an eCCM approach, CHWs are provided with a clear picture regarding the role of the eCCM solution, often resulting in buy-in from the end-users. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adherence" title="adherence">adherence</a>, <a href="https://publications.waset.org/abstracts/search?q=community%20health%20workers" title=" community health workers"> community health workers</a>, <a href="https://publications.waset.org/abstracts/search?q=developing%20countries" title=" developing countries"> developing countries</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20clinical%20decision%20support%20systems" title=" mobile clinical decision support systems"> mobile clinical decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=CDSS" title=" CDSS"> CDSS</a>, <a href="https://publications.waset.org/abstracts/search?q=service%20blueprint" title=" service blueprint"> service blueprint</a> </p> <a href="https://publications.waset.org/abstracts/37005/service-blueprint-for-improving-clinical-guideline-adherence-via-mobile-health-technology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37005.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">415</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">20857</span> A Decision Support System for Flight Disruptions Management</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Burak%20Erkayman">Burak Erkayman</a>, <a href="https://publications.waset.org/abstracts/search?q=Emin%20Gundogar"> Emin Gundogar</a>, <a href="https://publications.waset.org/abstracts/search?q=Hayrettin%20Evirgen"> Hayrettin Evirgen</a>, <a href="https://publications.waset.org/abstracts/search?q=Murat%20Sar%C4%B1"> Murat Sarı</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the increasing competition in recent years, airline companies tend to manage their operations aiming fewer losses in a robust manner. Airline operations are complex operations and have the necessity of being performed just in time and more knock-on relevant elements in the event of a disruption. In this study a knowledge based decision support system is suggested and software is developed. The developed software includes knowledge bases which are based on expert experience and government regulations, model bases and data bases. The results of the suggested approach are presented and improvable aspects of the approach are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge%20based%20systems" title="knowledge based systems">knowledge based systems</a>, <a href="https://publications.waset.org/abstracts/search?q=irregular%20operations" title=" irregular operations"> irregular operations</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20systems" title=" decision support systems"> decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=flight%20disruptions%20management" title=" flight disruptions management"> flight disruptions management</a> </p> <a href="https://publications.waset.org/abstracts/2659/a-decision-support-system-for-flight-disruptions-management" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2659.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">315</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">20856</span> Decision Support: How Explainable A.I. Can Improve Transparency and Trust with Human Users</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Devon%20Brown">Devon Brown</a>, <a href="https://publications.waset.org/abstracts/search?q=Liu%20Chunmei"> Liu Chunmei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper will present an analysis as part of the researchers dissertation topic focusing on the intersection of affective and analytical directed acyclic graphs (DAGs) in the context of Decision Support Systems (DSS). The researcher’s work involves analyzing decision theory models like Affective and Bayesian Decision theory models and how they could be implemented under an Affective Computing Framework using Information Fusion and Human-Centered Design. Additionally, the researcher is beginning research on an Affective-Analytic Decision Framework (AADF) model for their dissertation research and are looking to merge logic and analytic models with empathetic insights into affective DAGs. Data-collection efforts begin Fall 2024 and in preparation for the efforts this paper looks to analyze previous research in this area and introduce the AADF framework and propose conceptual models for consideration. For this paper, the research emphasis is placed on analyzing Bayesian networks and Markov models which offer probabilistic techniques during uncertainty in decision-making. Ideally, including affect into analytic models will ensure algorithms can increase user trust with algorithms by including emotional states and the user’s experience with the goal of developing emotionally intelligent A.I. systems that can start to navigate the complex fabric of human emotion during decision-making. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20systems" title="decision support systems">decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=explainable%20AI" title=" explainable AI"> explainable AI</a>, <a href="https://publications.waset.org/abstracts/search?q=HCAI%20techniques" title=" HCAI techniques"> HCAI techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=affective-analytical%20decision%20framework" title=" affective-analytical decision framework"> affective-analytical decision framework</a> </p> <a href="https://publications.waset.org/abstracts/190690/decision-support-how-explainable-ai-can-improve-transparency-and-trust-with-human-users" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190690.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">20</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20855</span> Decision Support for Modularisation: Engineering Construction Case Studies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rolla%20Monib">Rolla Monib</a>, <a href="https://publications.waset.org/abstracts/search?q=Chris%20Ian%20Goodier"> Chris Ian Goodier</a>, <a href="https://publications.waset.org/abstracts/search?q=Alistair%20Gibb"> Alistair Gibb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to investigate decision support strategies in the EC sector to determine the most appropriate degree of modularization. This is achieved through three oil and gas (O&G) and two power plant case studies via semi-structured interviews (n=59 and n=27, respectively), analysis of project documents, and case study-specific semi-structured validation interviews (n=12 and n=8). New terminology to distinguish degrees of modularization is proposed, along with a decision-making support checklist and a diagrammatic decision-making support figure. Results indicate that the EC sub-sectors were substantially more satisfied with the application of component, structural, or traditional modularization compared with system modularization for some types of modules. Key drivers for decisions on the degree of modularization vary across module types. This paper can help the EC sector determine the most suitable degree of modularization via a decision-making support strategy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=modularization" title="modularization">modularization</a>, <a href="https://publications.waset.org/abstracts/search?q=engineering%20construction" title=" engineering construction"> engineering construction</a>, <a href="https://publications.waset.org/abstracts/search?q=case%20study" title=" case study"> case study</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support" title=" decision support"> decision support</a> </p> <a href="https://publications.waset.org/abstracts/170602/decision-support-for-modularisation-engineering-construction-case-studies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170602.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">94</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">20854</span> Decision Making System for Clinical Datasets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Bharathiraja">P. Bharathiraja </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20making" title="decision making">decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=normalization" title=" normalization"> normalization</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20rule" title=" fuzzy rule"> fuzzy rule</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/31212/decision-making-system-for-clinical-datasets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31212.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">517</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">20853</span> A Neuro-Automata Decision Support System for the Control of Late Blight in Tomato Crops</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gizelle%20K.%20Vianna">Gizelle K. Vianna</a>, <a href="https://publications.waset.org/abstracts/search?q=Gustavo%20S.%20Oliveira"> Gustavo S. Oliveira</a>, <a href="https://publications.waset.org/abstracts/search?q=Gabriel%20V.%20Cunha"> Gabriel V. Cunha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title="artificial neural networks">artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=cellular%20automata" title=" cellular automata"> cellular automata</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20system" title=" decision support system"> decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=pattern%20recognition" title=" pattern recognition"> pattern recognition</a> </p> <a href="https://publications.waset.org/abstracts/63771/a-neuro-automata-decision-support-system-for-the-control-of-late-blight-in-tomato-crops" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63771.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">455</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">20852</span> Decision Support System for Tourism in Northern Part of Thailand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Katejarinporn%20Chaiya">Katejarinporn Chaiya</a>, <a href="https://publications.waset.org/abstracts/search?q=Thawit%20Janbanklong"> Thawit Janbanklong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purposes of this study were to design and find users’ satisfaction after using the decision support system for tourism in the Northern part of Thailand, which can provide tourists with touristic information and plan their personal voyage. Such information can be retrieved systematically based on personal budget and provinces. The samples of this study were five experts and users: 30 "white collars" in Bangkok. This decision support system was designed via ASP.NET. Its database was developed by using MySQL, for administrators to effectively manage the database. The application outcome revealed that the innovation works properly as sought in objectives. Specialists and white collars in Bangkok have evaluated the decision support system; the result was satisfactorily positive. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20Support%20System" title="decision Support System">decision Support System</a>, <a href="https://publications.waset.org/abstracts/search?q=ASP.NET" title=" ASP.NET"> ASP.NET</a>, <a href="https://publications.waset.org/abstracts/search?q=MySQL" title=" MySQL"> MySQL</a>, <a href="https://publications.waset.org/abstracts/search?q=white%20collars" title=" white collars"> white collars</a> </p> <a href="https://publications.waset.org/abstracts/11527/decision-support-system-for-tourism-in-northern-part-of-thailand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11527.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">358</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">20851</span> Patient-Specific Modeling Algorithm for Medical Data Based on AUC</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guilherme%20Ribeiro">Guilherme Ribeiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexandre%20Oliveira"> Alexandre Oliveira</a>, <a href="https://publications.waset.org/abstracts/search?q=Antonio%20Ferreira"> Antonio Ferreira</a>, <a href="https://publications.waset.org/abstracts/search?q=Shyam%20Visweswaran"> Shyam Visweswaran</a>, <a href="https://publications.waset.org/abstracts/search?q=Gregory%20Cooper"> Gregory Cooper</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=approach%20instance-based" title="approach instance-based">approach instance-based</a>, <a href="https://publications.waset.org/abstracts/search?q=area%20under%20the%20ROC%20curve" title=" area under the ROC curve"> area under the ROC curve</a>, <a href="https://publications.waset.org/abstracts/search?q=patient-specific%20decision%20path" title=" patient-specific decision path"> patient-specific decision path</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20predictions" title=" clinical predictions"> clinical predictions</a> </p> <a href="https://publications.waset.org/abstracts/35519/patient-specific-modeling-algorithm-for-medical-data-based-on-auc" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35519.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">478</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">20850</span> Selecting a Foreign Country to Build a Naval Base Using a Fuzzy Hybrid Decision Support System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Latif%20Yanar">Latif Yanar</a>, <a href="https://publications.waset.org/abstracts/search?q=Muammer%20Ka%C3%A7an"> Muammer Kaçan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Decision support systems are getting more important in many fields of science and technology and used effectively especially when the problems to be solved are complicated with many criteria. In this kind of problems one of the main challenges for the decision makers are that sometimes they cannot produce a countable data for evaluating the criteria but the knowledge and sense of experts. In recent years, fuzzy set theory and fuzzy logic based decision models gaining more place in literature. In this study, a decision support model to determine a country to build naval base is proposed and the application of the model is performed, considering Turkish Navy by the evaluations of Turkish Navy officers and academicians of international relations departments of various Universities located in Istanbul. The results achieved from the evaluations made by the experts in our model are calculated by a decision support tool named DESTEC 1.0, which is developed by the authors using C Sharp programming language. The tool gives advices to the decision maker using Analytic Hierarchy Process, Analytic Network Process, Fuzzy Analytic Hierarchy Process and Fuzzy Analytic Network Process all at once. The calculated results for five foreign countries are shown in the conclusion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20system" title="decision support system">decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=analytic%20hierarchy%20process" title=" analytic hierarchy process"> analytic hierarchy process</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20analytic%20hierarchy%20process" title=" fuzzy analytic hierarchy process"> fuzzy analytic hierarchy process</a>, <a href="https://publications.waset.org/abstracts/search?q=analytic%20network%20process" title=" analytic network process"> analytic network process</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20analytic%20network%20process" title=" fuzzy analytic network process"> fuzzy analytic network process</a>, <a href="https://publications.waset.org/abstracts/search?q=naval%20base" title=" naval base"> naval base</a>, <a href="https://publications.waset.org/abstracts/search?q=country%20selection" title=" country selection"> country selection</a>, <a href="https://publications.waset.org/abstracts/search?q=international%20relations" title=" international relations "> international relations </a> </p> <a href="https://publications.waset.org/abstracts/17037/selecting-a-foreign-country-to-build-a-naval-base-using-a-fuzzy-hybrid-decision-support-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17037.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">591</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">20849</span> Efficient Design of Distribution Logistics by Using a Model-Based Decision Support System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20Becker">J. Becker</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Arnold"> R. Arnold</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structures. Combined with qualitative measures the decision support system will contribute to a more efficient design of distribution logistics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20system" title="decision support system">decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=distribution%20logistics" title=" distribution logistics"> distribution logistics</a>, <a href="https://publications.waset.org/abstracts/search?q=potential%20analyses" title=" potential analyses"> potential analyses</a>, <a href="https://publications.waset.org/abstracts/search?q=supply%20chain%20management" title=" supply chain management"> supply chain management</a> </p> <a href="https://publications.waset.org/abstracts/44230/efficient-design-of-distribution-logistics-by-using-a-model-based-decision-support-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44230.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">406</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">20848</span> Comparing the ‘Urgent Community Care Team’ Clinical Referrals in the Community with Suggestions from the Clinical Decision Support Software Dem DX</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Tariq">R. Tariq</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Lee"> R. Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Additional demands placed on senior clinical teams with ongoing COVID-19 management has accelerated the need to harness the wider healthcare professional resources and upskill them to take on greater clinical responsibility safely. The UK NHS Long Term Plan (2019)¹ emphasises the importance of expanding Advanced Practitioners’ (APs) roles to take on more clinical diagnostic responsibilities to cope with increased demand. In acute settings, APs are often the first point of care for patients and require training to take on initial triage responsibilities efficiently and safely. Critically, their roles include determining which onward services the patients may require, and assessing whether they can be treated at home, avoiding unnecessary admissions to the hospital. Dem Dx is a Clinical Reasoning Platform (CRP) that claims to help frontline healthcare professionals independently assess and triage patients. It guides the clinician from presenting complaints through associated symptoms to a running list of differential diagnoses, media, national and institutional guidelines. The objective of this study was to compare the clinical referral rates and guidelines adherence registered by the HMR Urgent Community Care Team (UCCT)² and Dem Dx recommendations using retrospective cases. Methodology: 192 cases seen by the UCCT were anonymised and reassessed using Dem Dx clinical pathways. We compared the UCCT’s performance with Dem Dx regarding the appropriateness of onward referrals. We also compared the clinical assessment regarding adherence to NICE guidelines recorded on the clinical notes and the presence of suitable guidance in each case. The cases were audited by two medical doctors. Results: Dem Dx demonstrated appropriate referrals in 85% of cases, compared to 47% in the UCCT team (p<0.001). Of particular note, Dem Dx demonstrated an almost 65% (p<0.001) improvement in the efficacy and appropriateness of referrals in a highly experienced clinical team. The effectiveness of Dem Dx is in part attributable to the relevant NICE and local guidelines found within the platform's pathways and was found to be suitable in 86% of cases. Conclusion: This study highlights the potential of clinical decision support, as Dem Dx, to improve the quality of onward clinical referrals delivered by a multidisciplinary team in primary care. It demonstrated that it could support healthcare professionals in making appropriate referrals, especially those that may be overlooked by providing suitable clinical guidelines directly embedded into cases and clear referral pathways. Further evaluation in the clinical setting has been planned to confirm those assumptions in a prospective study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=advanced%20practitioner" title="advanced practitioner">advanced practitioner</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20reasoning" title=" clinical reasoning"> clinical reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision-making" title=" clinical decision-making"> clinical decision-making</a>, <a href="https://publications.waset.org/abstracts/search?q=management" title=" management"> management</a>, <a href="https://publications.waset.org/abstracts/search?q=multidisciplinary%20team" title=" multidisciplinary team"> multidisciplinary team</a>, <a href="https://publications.waset.org/abstracts/search?q=referrals" title=" referrals"> referrals</a>, <a href="https://publications.waset.org/abstracts/search?q=triage" title=" triage"> triage</a> </p> <a href="https://publications.waset.org/abstracts/141997/comparing-the-urgent-community-care-team-clinical-referrals-in-the-community-with-suggestions-from-the-clinical-decision-support-software-dem-dx" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141997.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">20847</span> Decision Support System for Examination Selection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Katejarinporn%20Chaiya">Katejarinporn Chaiya</a>, <a href="https://publications.waset.org/abstracts/search?q=Jarumon%20Nookong"> Jarumon Nookong</a>, <a href="https://publications.waset.org/abstracts/search?q=Nutthapat%20Kaewrattanapat"> Nutthapat Kaewrattanapat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purposes of this research were to develop and find users’ satisfaction after using the Decision Support System for Examination Selection. This research presents the design of information systems. In order to find the necessary examination of the statistics. Based on the examination of the candidate and then taking the easy difficulty setting statistics applied to the test. In addition, research has also made performance appraisals from experts and user satisfaction. By results of analysis showed that the performance appraisals from experts on the system as a whole and at a good level. mean was 3.44 and S.D. was 0.55 and user satisfaction per system as a whole and the good level mean was 3.37 and S.D. was 0.42 can conclude that effective systems are in a good level. Work has been completed in accordance with the scope of work. The website used developing this project is PHP, MySQL.5.0.45 for database. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=secision%20support%20system" title="secision support system">secision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=examination" title=" examination"> examination</a>, <a href="https://publications.waset.org/abstracts/search?q=PHP" title=" PHP"> PHP</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20systems" title=" information systems"> information systems</a> </p> <a href="https://publications.waset.org/abstracts/13308/decision-support-system-for-examination-selection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13308.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">449</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">20846</span> Using the Clinical Decision Support Platform, Dem DX, to Assess the ‘Urgent Community Care Team’s Notes Regarding Clinical Assessment, Management, and Healthcare Outcomes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Tariq">R. Tariq</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Lee"> R. Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Heywood, Middleton & Rochdale Urgent Community Care Team (UCCT)1 is a great example of using a multidisciplinary team to cope with demand. The service reduces unnecessary admissions to hospitals and ensures that patients can leave the hospital quicker by making care more readily available within the community and patient’s homes. The team comprises nurses, community practitioners, and allied health professions, including physiotherapy, occupational therapy, pharmacy, and GPs. The main challenge for a team with a range of experiences and skill sets is to maintain consistency of care, which technology can help address. Allied healthcare professionals (HCPs) are often used in expanded roles with duties mainly involving patient consultations and decision making to ease pressure on doctors. The Clinical Reasoning Platform (CRP) Dem Dx is used to support new as well as experienced professionals in the decision making process. By guiding HCPs through diagnosing patients from an expansive directory of differential diagnoses, patients can receive quality care in the community. Actions on the platform are determined using NICE guidelines along with local guidance influencing the assessment and management of a patient. Objective: To compare the clinical assessment, decisions, and actions taken by the UCCT multidisciplinary team in the community and Dem Dx, using retrospective clinical cases. Methodology: Dem Dx was used to analyse 192 anonymised cases provided by the HMR UCCT. The team’s performance was compared with Dem Dx regarding the quality of the documentation of the clinical assessment and the next steps on the patient’s journey, including the initial management, actions, and any onward referrals made. The cases were audited by two medical doctors. Results: The study found that the actions outlined by the Dem Dx platform were appropriate in almost 87% of cases. When in a direct comparison between DemDX and the actions taken by the clinical team, it was found that the platform was suitable 83% (p<0.001) of the time and could lead to a potential improvement of 66% in the assessment and management of cases. Dem Dx also served to highlight the importance of comprehensive and high quality clinical documentation. The quality of documentation of cases by UCCT can be improved to provide a detailed account of the assessment and management process. By providing step-by-step guidance and documentation at every stage, Dem Dx may ensure that legal accountability has been fulfilled. Conclusion: With the ever expanding workforce in the NHS, technology has become a key component in driving healthcare outcomes. To improve healthcare provision and clinical reasoning, a decision support platform can be integrated into HCPs’ clinical practice. Potential assistance with clinical assessments, the most appropriate next step and actions in a patient’s care, and improvements in the documentation was highlighted by this retrospective study. A further study has been planned to ascertain the effectiveness of improving outcomes using the clinical reasoning platform within the clinical setting by clinicians. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=allied%20health%20professional" title="allied health professional">allied health professional</a>, <a href="https://publications.waset.org/abstracts/search?q=assessment" title=" assessment"> assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20reasoning" title=" clinical reasoning"> clinical reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20records" title=" clinical records"> clinical records</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20decision-making" title=" clinical decision-making"> clinical decision-making</a>, <a href="https://publications.waset.org/abstracts/search?q=ocumentation" title=" ocumentation"> ocumentation</a> </p> <a href="https://publications.waset.org/abstracts/141995/using-the-clinical-decision-support-platform-dem-dx-to-assess-the-urgent-community-care-teams-notes-regarding-clinical-assessment-management-and-healthcare-outcomes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141995.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">164</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">20845</span> Intelligent Decision Support for Wind Park Operation: Machine-Learning Based Detection and Diagnosis of Anomalous Operating States</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Angela%20Meyer">Angela Meyer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anomaly%20detection" title="anomaly detection">anomaly detection</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support" title=" decision support"> decision support</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=monitoring" title=" monitoring"> monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20optimization" title=" performance optimization"> performance optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbines" title=" wind turbines "> wind turbines </a> </p> <a href="https://publications.waset.org/abstracts/118859/intelligent-decision-support-for-wind-park-operation-machine-learning-based-detection-and-diagnosis-of-anomalous-operating-states" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118859.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">167</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">20844</span> Clinical Advice Services: Using Lean Chassis to Optimize Nurse-Driven Telephonic Triage of After-Hour Calls from Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eric%20Lee%20G.%20Escobedo-Wu">Eric Lee G. Escobedo-Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Nidhi%20Rohatgi"> Nidhi Rohatgi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fouzel%20Dhebar"> Fouzel Dhebar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is challenging for patients to navigate through healthcare systems after-hours. This leads to delays in care, patient/provider dissatisfaction, inappropriate resource utilization, readmissions, and higher costs. It is important to provide patients and providers with effective clinical decision-making tools to allow seamless connectivity and coordinated care. In August 2015, patient-centric Stanford Health Care established Clinical Advice Services (CAS) to provide clinical decision support after-hours. CAS is founded on key Lean principles: Value stream mapping, empathy mapping, waste walk, takt time calculations, standard work, plan-do-check-act cycles, and active daily management. At CAS, Clinical Assistants take the initial call and manage all non-clinical calls (e.g., appointments, directions, general information). If the patient has a clinical symptom, the CAS nurses take the call and utilize standardized clinical algorithms to triage the patient to home, clinic, urgent care, emergency department, or 911. Nurses may also contact the on-call physician based on the clinical algorithm for further direction and consultation. Since August 2015, CAS has managed 228,990 calls from 26 clinical specialties. Reporting is built into the electronic health record for analysis and data collection. 65.3% of the after-hours calls are clinically related. Average clinical algorithm adherence rate has been 92%. An average of 9% of calls was escalated by CAS nurses to the physician on call. An average of 5% of patients was triaged to the Emergency Department by CAS. Key learnings indicate that a seamless connectivity vision, cascading, multidisciplinary ownership of the problem, and synergistic enterprise improvements have contributed to this success while striving for continuous improvement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=after%20hours%20phone%20calls" title="after hours phone calls">after hours phone calls</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20advice%20services" title=" clinical advice services"> clinical advice services</a>, <a href="https://publications.waset.org/abstracts/search?q=nurse%20triage" title=" nurse triage"> nurse triage</a>, <a href="https://publications.waset.org/abstracts/search?q=Stanford%20Health%20Care" title=" Stanford Health Care"> Stanford Health Care</a> </p> <a href="https://publications.waset.org/abstracts/90272/clinical-advice-services-using-lean-chassis-to-optimize-nurse-driven-telephonic-triage-of-after-hour-calls-from-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90272.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">174</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">20843</span> Decision Support Tool for Green Roofs Selection: A Multicriteria Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=I.%20Teot%C3%B3nio">I. Teotónio</a>, <a href="https://publications.waset.org/abstracts/search?q=C.O.%20Cruz"> C.O. Cruz</a>, <a href="https://publications.waset.org/abstracts/search?q=C.M.%20Silva"> C.M. Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Manso"> M. Manso</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diverse stakeholders show different concerns when choosing green roof systems. Also, green roof solutions vary in their cost and performance. Therefore, decision-makers continually face the difficult task of balancing benefits against green roofs costs. Decision analysis methods, as multicriteria analysis, can be used when the decision‑making process includes different perspectives, multiple objectives, and uncertainty. The present study adopts a multicriteria decision model to evaluate the installation of green roofs in buildings, determining the solution with the best trade-off between costs and benefits in agreement with the preferences of the users/investors. This methodology was applied to a real decision problem, assessing the preferences between different green roof systems in an existing building in Lisbon. This approach supports the decision-making process on green roofs and enables robust and informed decisions on urban planning while optimizing buildings retrofitting. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20making" title="decision making">decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=green%20roofs" title=" green roofs"> green roofs</a>, <a href="https://publications.waset.org/abstracts/search?q=investors%20preferences" title=" investors preferences"> investors preferences</a>, <a href="https://publications.waset.org/abstracts/search?q=multicriteria%20analysis" title=" multicriteria analysis"> multicriteria analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable%20development" title=" sustainable development"> sustainable development</a> </p> <a href="https://publications.waset.org/abstracts/115903/decision-support-tool-for-green-roofs-selection-a-multicriteria-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115903.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">184</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support%20systems&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=clinical%20decision%20support%20systems&page=3">3</a></li> <li class="page-item"><a class="page-link" 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