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Big Data Analytics for Healthcare: Datasets, Techniques, Life Cycles, Management, and Applications

Big Data Analytics for Healthcare: Datasets, Techniques, Life Cycles, Management, and Applications

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Big Data Analytics for Healthcare: Datasets, Techniques, Life Cycles, Management, and Applications

Big Data Analytics for Healthcare: Datasets, Techniques, Life Cycles, Management, and Applications

Category

Data Analysis

Big Data

Healthcare

Author

Pantea Keikhosrokiani

Publication

Academic Press

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Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work.

Presents theories, methods and approaches in which data analytic techniques are used for medical data
Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases
Discusses social, behavioral, and medical fake news analytics for medical information systems

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ISBN-13

978-0323919074

Publisher

Academic Press

Price

148.16

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PDF

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Pantea Keikhosrokiani

Pantea Keikhosrokiani

Review

Brings practical and updated information about big data techniques applied to biomedical sciences --This text refers to the paperback edition.

From the Back Cover

Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases.The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths.It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. --This text refers to the paperback edition.

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