Overview
- Provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics
- Reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area
- Offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges
- Presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics
Part of the book series: Learning and Analytics in Intelligent Systems (LAIS, volume 13)
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Table of contents (16 chapters)
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Front Matter
Keywords
About this book
This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.
Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning with Health Care Perspective
Book Subtitle: Machine Learning and Healthcare
Editors: Vishal Jain, Jyotir Moy Chatterjee
Series Title: Learning and Analytics in Intelligent Systems
DOI: https://doi.org/10.1007/978-3-030-40850-3
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-40849-7Published: 10 March 2020
Softcover ISBN: 978-3-030-40852-7Published: 10 March 2021
eBook ISBN: 978-3-030-40850-3Published: 09 March 2020
Series ISSN: 2662-3447
Series E-ISSN: 2662-3455
Edition Number: 1
Number of Pages: X, 415
Number of Illustrations: 70 b/w illustrations, 117 illustrations in colour
Topics: Computational Intelligence, Biomedical Engineering and Bioengineering