Overview
- Presents recent research on all aspects of machine learning and data mining for health care
- Focuses on general algorithms that can handle multiple sources of complex data in medical research databases
- Includes various successful machine learning algorithms for health care as well as applications and descriptions of actual systems
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 186)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (10 chapters)
-
Front Matter
-
Deep Features and Their Fusion
-
Front Matter
-
-
Augmentation
-
Front Matter
-
-
Medical Applications and Reviews
-
Front Matter
-
-
Ethical Considerations
-
Front Matter
-
Keywords
About this book
This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to illustrate the five major ways deep learners can be utilized: 1) by training a deep learner from scratch (chapters provide tips for handling imbalances and other problems with the medical data); 2) by implementing transfer learning from a pre-trained deep learner and extracting deep features for different CNN layers that can be fed into simpler classifiers, such as the support vector machine; 3) by fine-tuning one or more pre-trained deep learners on an unrelated dataset so that they are able to identify novel medical datasets; 4) by fusing different deep learner architectures; and 5) by combining the above methods to generate a variety of more elaborate ensembles. This book is a value resource for anyone involved in engineering deep learners for medical applications as well as to those interested in learning more about the current techniques in this exciting field. A number of chapters provide source code that can be used to investigate topics further or to kick-start new projects.
Editors and Affiliations
Bibliographic Information
Book Title: Deep Learners and Deep Learner Descriptors for Medical Applications
Editors: Loris Nanni, Sheryl Brahnam, Rick Brattin, Stefano Ghidoni, Lakhmi C. Jain
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-030-42750-4
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-42748-1Published: 16 May 2020
eBook ISBN: 978-3-030-42750-4Published: 15 May 2020
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XI, 284
Number of Illustrations: 59 b/w illustrations, 51 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Health Informatics, Biomedical Engineering and Bioengineering