Machine Learning in Biomedical and Health Informatics

Current Applications and Challenges

Discusses ML in predictive health analytics, pandemic management, AI ethics, application and integration of IoT and ML for effective healthcare, and more. Covers a range of bioinformatics tools and methods and their relation to drug designing and screening using ML.

Machine learning is playing an indispensable role in framing clinical decisions and enhancing accuracy. This new book offers a comprehensive take on the field of biomedical and health informatics, discussing topics that include predictive health analytics, pandemic management, AI ethics, application and integration of Internet of Things and machine learning for effective healthcare, and more. The book covers a range of bioinformatics tools and methods and their relation to drug designing and drug screening using ML. Several chapters cover clustering techniques and other methods for analyzing human heart-related disorders. The authors also explore the use of ML in creating adaptive therapies for using chemotherapy and androgen deprivation therapy for prostate cancer and for tracking diseases such as Parkinson’s Speech, Covid-19, and others. Case studies are included that demonstrate the practical use of ML in healthcare informatics.

Contributor: Sudip Kumar Sahana (Edited by), Rajendrani Mukherjee (Edited by), Panchali Datta Choudhury (Edited by), Prasenjit Chatterjee (Edited by)

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