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"This book establishes a convergence in thinking between knowledge management and knowledge engineering healthcare applications"--Provided by publisher.
Biomedical Information Technology, Second Edition, contains practical, integrated clinical applications for disease detection, diagnosis, surgery, therapy and biomedical knowledge discovery, including the latest advances in the field, such as biomedical sensors, machine intelligence, artificial intelligence, deep learning in medical imaging, neural networks, natural language processing, large-scale histopathological image analysis, virtual, augmented and mixed reality, neural interfaces, and data analytics and behavioral informatics in modern medicine. The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organiz...
This book discusses 120 types of natural, small-molecule drugs derived from plants. They are grouped into 7 parts according their clinical uses, such as drugs for cardiovascular diseases, for metabolic diseases, for neuropsychiatric diseases, for immune-mediated inflammatory diseases, anti-tumor drugs, and drugs for parasites and bacterial infection. Each chapter systematically summarizes one drug, including its physicochemical properties, sources, pharmacological effects and clinical applications. To help readers understand the drug better, the research and pharmacological activity for each drug is also described, which serves as a salutary lesson for future drug development. Written by frontline researchers, teachers and clinicians working in field of pharmacy and pharmacology it provides an overview of natural, small-molecule drugs derived from plants for researchers in the field.
Biomedical Diagnostics and Clinical Technologies: Applying High-Performance Cluster and Grid Computing disseminates knowledge regarding high performance computing for medical applications and bioinformatics. This critical reference source contains a valuable collection of cutting-edge research chapters for those working in the broad field of medical informatics and bioinformatics.
The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.