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Deep Learning. --- Precision Medicine. --- Patient-Specific Modeling. --- Decision Support Systems, Clinical. --- Clinical Decision Support --- Decision Support, Clinical --- Clinical Decision Support System --- Clinical Decision Support Systems --- Clinical Decision Supports --- Decision Supports, Clinical --- Support, Clinical Decision --- Supports, Clinical Decision --- Clinical Decision-Making --- Patient-Specific Computational Modeling --- Physiome --- Computational Modeling, Patient-Specific --- Modeling, Patient-Specific --- Patient Specific Computational Modeling --- Patient Specific Modeling --- Physiomes --- Models, Biological --- Precision Medicine --- P Health --- P-Health --- Personalized Medicine --- Theranostics --- Individualized Medicine --- Predictive Medicine --- Medicine, Individualized --- Medicine, Personalized --- Medicine, Precision --- Medicine, Predictive --- Theranostic --- Pharmacogenomic Variants --- Pharmacogenetics --- Patient-Specific Modeling --- Hierarchical Learning --- Learning, Deep --- Learning, Hierarchical --- Precision medicine --- Deep learning (Machine learning) --- Artificial intelligence --- Data processing. --- Medical applications.

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This edited book contains twelve studies, large and pilots, in five main categories: (i) adaptive imputation to increase the density of clinical data for improving downstream modeling; (ii) machine-learning-empowered diagnosis models; (iii) machine learning models for outcome prediction; (iv) innovative use of AI to improve our understanding of the public view; and (v) understanding of the attitude of providers in trusting insights from AI for complex cases. This collection is an excellent example of how technology can add value in healthcare settings and hints at some of the pressing challenges in the field. Artificial intelligence is gradually becoming a go-to technology in clinical care; therefore, it is important to work collaboratively and to shift from performance-driven outcomes to risk-sensitive model optimization, improved transparency, and better patient representation, to ensure more equitable healthcare for all.

machine learning-enabled decision support system --- improving diagnosis accuracy --- Bayesian network --- bariatric surgery --- health-related quality of life --- comorbidity --- voice change --- larynx cancer --- machine learning --- deep learning --- voice pathology classification --- imputation --- electronic health records --- EHR --- laboratory measures --- medical informatics --- inflammatory bowel disease --- C. difficile infection --- osteoarthritis --- complex diseases --- healthcare --- artificial intelligence --- interpretable machine learning --- explainable machine learning --- septic shock --- clinical decision support system --- electronic health record --- cerebrovascular disorders --- stroke --- SARS-CoV-2 --- COVID-19 --- cluster analysis --- risk factors --- ischemic stroke --- outcome prediction --- recurrent stroke --- cardiac ultrasound --- echocardiography --- portable ultrasound --- aneurysm surgery --- temporary artery occlusion --- clipping time --- artificial neural network --- digital imaging --- monocytes --- promonocytes and monoblasts --- chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML) for acute monoblastic leukemia and acute monocytic leukemia --- concordance between hematopathologists --- mechanical ventilation --- respiratory failure --- ADHD --- social media --- Twitter --- pharmacotherapy --- stimulants --- alpha-2-adrenergic agonists --- non-stimulants --- trust --- passive adherence --- human factors

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This book examines the nature of medical knowledge, how it is obtained, and how it can be used for decision support. It provides complete coverage of computational approaches to clinical decision-making. Chapters discuss data integration into healthcare information systems and delivery to point of care for providers, as well as facilitation of direct to consumer access. A case study section highlights critical lessons learned, while another portion of the work examines biostatistical methods including data mining, predictive modelling, and analysis. This book additionally addresses organizatio

Clinical medicine -- Decision making -- Data processing. --- Diagnosis -- Decision making -- Data processing. --- Diagnosis --- Clinical medicine --- Thinking --- Medicine --- Patient Care Management --- Information Systems --- Technology --- Medical Records Systems, Computerized --- Medical Informatics --- Organization and Administration --- Health Care Quality, Access, and Evaluation --- Learning --- Health Occupations --- Information Science --- Health Services Administration --- Health Care --- Technology, Industry, and Agriculture --- Mental Processes --- Medical Records --- Records as Topic --- Disciplines and Occupations --- Psychological Phenomena and Processes --- Technology, Industry, Agriculture --- Psychiatry and Psychology --- Data Collection --- Epidemiologic Methods --- Investigative Techniques --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Delivery of Health Care --- Problem Solving --- Clinical Medicine --- Medical Informatics Applications --- Electronic Health Records --- Organizational Innovation --- Automation --- Decision Support Systems, Clinical --- Health & Biological Sciences --- Radiology, MRI, Ultrasonography & Medical Physics --- Decision making --- Data processing --- Data processing. --- Clinical Decision Support --- Decision Support, Clinical --- Clinical Decision Support Systems --- Clinical Decision Supports --- Decision Supports, Clinical --- Support, Clinical Decision --- Supports, Clinical Decision --- Clinical Decision-Making --- Medicine, Clinical --- Diseases --- Examinations, Medical (Diagnosis) --- Medical diagnosis --- Medical examinations (Diagnosis) --- Medical tests (Diagnosis) --- Prognosis --- Symptoms --- Testing --- Clinical Decision Support System

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"Clinical Decision Support and Beyond: Progress and Opportunities in Knowledge-Enhanced Health and Healthcare, now in its third edition, discusses the underpinnings of effective, reliable, and easy-to-use clinical decision support systems at the point of care as a productive way of managing the flood of data, knowledge, and misinformation when providing patient care. Incorporating CDS into electronic health record systems has been underway for decades; however its complexities, costs, and user resistance have lagged its potential. Thus it is of utmost importance to understand the process in detail, to take full advantage of its capabilities. The book expands and updates the content of the previous edition, and discusses topics such as integration of CDS into workflow, context-driven anticipation of needs for CDS, new forms of CDS derived from data analytics, precision medicine, population health, integration of personal monitoring, and patient-facing CDS. In addition, it discusses population health management, public health CDS and CDS to help reduce health disparities. It is a valuable resource for clinicians, practitioners, students and members of medical and biomedical fields who are interested to learn more about the potential of clinical decision support to improve health and wellness and the quality of health care. Presents an overview and details of the current state of the art and usefulness of clinical decision support, and how to utilize these capabilities Explores the technological underpinnings for developing, managing, and sharing knowledge resources and deploying them as CDS or for other uses Discusses the current drivers and opportunities that are expanding the prospects for use of knowledge to enhance health and healthcare"-- From ProQuest Ebook Central.

Decision Support Systems, Clinical --- Clinical medicine --- Decision making --- Clinical Decision Support --- Decision Support, Clinical --- Clinical Decision Support System --- Clinical Decision Support Systems --- Clinical Decision Supports --- Decision Supports, Clinical --- Support, Clinical Decision --- Supports, Clinical Decision --- Clinical Decision-Making --- Diagnosis --- Problem solving. --- Data processing. --- Methodology --- Psychology --- Executive functions (Neuropsychology) --- Diseases --- Examinations, Medical (Diagnosis) --- Medical diagnosis --- Medical examinations (Diagnosis) --- Medical tests (Diagnosis) --- Prognosis --- Symptoms --- Medicine, Clinical --- Medicine --- Testing --- Problem Solving --- Electronic Health Records. --- Organizational Innovation. --- Automation. --- Medical Informatics --- Medical Informatics Applications --- trends. --- Application, Medical Informatics --- Applications, Medical Informatics --- Informatics Applications, Medical --- Informatics Application, Medical --- Medical Informatics Application --- Biomedical Engineering --- Computer Science, Medical --- Health Informatics --- Health Information Technology --- Informatics, Clinical --- Informatics, Medical --- Information Science, Medical --- Clinical Informatics --- Medical Computer Science --- Medical Information Science --- Health Information Technologies --- Informatics, Health --- Information Technology, Health --- Medical Computer Sciences --- Medical Information Sciences --- Science, Medical Computer --- Technology, Health Information --- Computational Biology --- Biomedical Technology --- American Recovery and Reinvestment Act --- Automations --- Change, Organizational --- Innovation, Organizational --- Organizational Change --- Changes, Organizational --- Innovations, Organizational --- Organizational Changes --- Organizational Innovations --- Computerized Medical Record --- Computerized Medical Records --- Electronic Health Record --- Medical Record, Computerized --- Medical Records, Computerized --- Electronic Health Record Data --- Electronic Medical Record --- Electronic Medical Records --- Health Record, Electronic --- Health Records, Electronic --- Medical Record, Electronic --- Medical Records, Electronic --- Medical Record Linkage --- Executive Function --- Organizational change.