Data Analytics in Biomedical Engineering and Healthcare

Download or Read online Data Analytics in Biomedical Engineering and Healthcare full in PDF, ePub and kindle. This book written by Kun Chang Lee and published by Academic Press which was released on 23 October 2020 with total pages 292. We cannot guarantee that Data Analytics in Biomedical Engineering and Healthcare book is available in the library, click Get Book button to download or read online books. Join over 650.000 happy Readers and READ as many books as you like.

Data Analytics in Biomedical Engineering and Healthcare
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Publisher : Academic Press
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ISBN : 9780128193150
Pages : 292 pages
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Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks. Examines the development and application of data analytics applications in biomedical data Presents innovative classification and regression models for predicting various diseases Discusses genome structure prediction using predictive modeling Shows readers how to develop clinical decision support systems Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks

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 in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data

GET BOOK!
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