Data Driven Science for Clinically Actionable Knowledge in Diseases (Analytics and AI for Healthcare)

By: Daniel R. Catchpoole and Simeon J. Simoff and Paul J. Kennedy and Quang Vinh Nguyen

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Synopsis: Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.

Book Quality:: Publisher Quality
ISBN-13:: 9781003801689
Related ISBNs:: 9781032273518, 9781003292357, 9781032273532
Publisher:: CRC Press
Date of Addition:: 12/06/23
Copyrighted By:: selection and editorial matter, Daniel R. Catchpoole, Simeon J. Simoff, Paul J. Kennedy, and Quang Vinh Nguyen
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Business and Finance, Medicine
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Daniel R. Catchpoole
Edited by:: Simeon J. Simoff
Edited by:: Paul J Kennedy
Edited by:: Quang Vinh Nguyen