Vijay Kumar

Kun Chang Lee

Pijush Samui

Sanjiban Sekhar Roy

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

Tai-hoon Kim

Hojjat Adeli

Byeong-Ho Kang

Wai-chi Fang

Jianhua Ma

Byungjoo Park

Frode Eika Sandnes

This book constitutes the refereed proceedings of the International Conference, UNESST 2011, held as Part of the Future Generation Information Technology Conference, FGIT 2011, Jeju Island, Korea, in December 2011. The papers presented were carefully reviewed and selected from numerous submissions and focuse on the various aspects of u- and e-service, science and technology.

International Conference, UNESST 2011, Held as Part of the Future Generation Information Technology Conference, FGIT 2011, in Conjunction with GDC 2011, Jeju Island, Korea, December 8-10, 2011. Proceedings

U- and E-Service, Science and Technology

Kun Chang Lee

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