Deep Learners and Deep Learner Descriptors for Medical Applications
Synopsis
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.Book details
- Edition:
- 1st ed. 2020
- Series:
- Intelligent Systems Reference Library (Book 186)
- Author:
- Lakhmi C. Jain, Sheryl Brahnam, Loris Nanni, Stefano Ghidoni, Rick Brattin
- ISBN:
- 9783030427504
- Related ISBNs:
- 9783030427481
- Publisher:
- Springer International Publishing
- Pages:
- N/A
- Reading age:
- Not specified
- Includes images:
- Yes
- Date of addition:
- 2022-07-25
- Usage restrictions:
- Copyright
- Copyright date:
- 2020
- Copyright by:
- Springer Nature Switzerland AG
- Adult content:
- No
- Language:
- English
- Categories:
- Computers and Internet, Medicine, Nonfiction, Science, Technology