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Data Analytics in Biomedical Engineering and Healthcare

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning;

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Smart Computational Intelligence in Biomedical and Health Informatics

Covers evolutionary approaches to solve optimization problems in biomedical engineering. Discusses IoT, Cloud computing, data analytics;

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Green Computing and Predictive Analytics for Healthcare

technologies. Features: Biomedical data monitoring under the Internet of Things Environment data sensing and analyzing;

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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization;

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Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering;

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Heterogeneous Data Management, Polystores, and Analytics for Healthcare

; Deep Learning based Biomedical Data Analytics; NLP based Learning from Unstructured Data; Biomedical Data Modelling and Prediction.;

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Trends and Applications in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and;

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Data Management and Analytics for Medicine and Healthcare

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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Translational Bioinformatics Applications in Healthcare

voluminous biomedical and genomic data into 4P healthcare (proactive, predictive, preventive, and participatory). Translational Bioinformatics;

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Handbook of Computational Intelligence in Biomedical Engineering and Healthcare

in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical;

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The Role of the Internet of Things (IoT) in Biomedical Engineering

healthcare monitoring as well as for remote healthcare, data communication, monitoring, and diagnosis.;

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Data Management and Analytics for Medicine and Healthcare

; biomedical data management and Integration; online mining of Health related data; and clinical data analytics.;

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Healthcare Analytics Knowledge

sections, Part I features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological;

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Heterogeneous Data Management, Polystores, and Analytics for Healthcare

Discovery from Unstructured Biomedical Data; Blockchain and Privacy Preserving Data Management.;

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Deep Learning for Data Analytics

of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications;

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Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics

, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our;

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Biomedical Data Management and Graph Online Querying

information retrieval and data analytics for electronic medical records; data management and visualization of medical data; biomedical data sharing;

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Terahertz Biomedical and Healthcare Technologies

Terahertz Biomedical and Healthcare Technologies: Materials to Devices reviews emerging advances in terahertz biomedical and healthcare;

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Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications

This book constitutes the proceedings of the 7th International Conference on Future Data and Security Engineering, FDSE 2020, held in Quy;

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Transforming Healthcare Analytics

intelligence for making better healthcare decisions. Identifying patterns and correlations contained in complex health data, analytics has applications;

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Healthcare Data Analytics and Management

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools;

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Handbook of Artificial Intelligence in Biomedical Engineering

, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume;

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Leveraging Biomedical and Healthcare Data

Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic;

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Healthcare Analytics Made Simple

Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python;

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Strategies in Biomedical Data Science

An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals;

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Brain Informatics and Health

; brain data analytics; health data analytics; brain informatics and data management; semantic aspects of biomedical analytics; healthcare;

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Healthcare Data Analytics

At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many;

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