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Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic;
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Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning;
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in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical;
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An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals;
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healthcare monitoring as well as for remote healthcare, data communication, monitoring, and diagnosis.;
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The healthcare industry is in a state of accelerated transition. The proliferation of data and its assimilation, access, use, and security;
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The healthcare industry is in a state of accelerated transition. The proliferation of data and its assimilation, access, use, and security;
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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization;
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decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be;
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decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be;
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Discovery from Unstructured Biomedical Data; Blockchain and Privacy Preserving Data Management.;
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carefully reviewed and selected from 11 initial submissions. The papers are organized in topical sections on knowledge discovery of biomedical data;
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Covers evolutionary approaches to solve optimization problems in biomedical engineering. Discusses IoT, Cloud computing, data analytics;
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, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume;
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Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering;
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; Deep Learning based Biomedical Data Analytics; NLP based Learning from Unstructured Data; Biomedical Data Modelling and Prediction.;
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labeling for biomedical visual data analysis and understanding; advanced ICT for medicine and healthcare; and healthcare support systems;
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This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical;
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This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical;
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and Biology, discusses and reviews biomedical data resources, data standards, data organization, medicolegal and ethical conduct for data;
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Biomedical Engineering, IWBBIO 2017, held in Granada, Spain, in April 2017. The 122 papers presented were carefully reviewed and selected from;
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Biomedical Engineering, IWBBIO 2017, held in Granada, Spain, in April 2017. The 122 papers presented were carefully reviewed and selected from;
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Terahertz Biomedical and Healthcare Technologies: Materials to Devices reviews emerging advances in terahertz biomedical and healthcare;
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; biomedical data management and Integration; online mining of Health related data; and clinical data analytics.;
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biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it;
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biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it;
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For one-quarter/semester courses in Medical Ethics, Biomedical Ethics, Allied Healthcare, Healthcare Ethics, and Healthcare Law and Ethics;
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