Deep learning for medical decision support systems
- Responsibility
- Utku Kose, Omer Deperlioglu, Jafar Alzubi, Bogdan Patrut.
- Digital
- text file; PDF
- Edition
- 1st ed. 2021.
- Publication
- Singapore : Springer, [2021]
- Physical description
- 1 online resource (XVIII, 171 pages) : 63 illustrations, 60 illustrations in color.
- Series
- Studies in computational intelligence.
Online
Available online
More options
Description
Creators/Contributors
- Author/Creator
- Kose, Utku, 1985- author.
- Contributor
- Deperlioglu, Omer, 1967- author.
- Alzubi, Jafar, author.
- Patrut, Bogdan, author.
Contents/Summary
- Bibliography
- Includes bibliographical references.
- Contents
-
- 1.
- Deep Learning for Innovative Medical Decision Support
- 2.
- Deep Learning and Image Analysis for Medical Decision Support
- 3.
- Deep Learning Oriented Systems for Medical Education
- 4.
- Hybrid Deep Systems for Medical Education and Decision Support
- 5.
- Deep Learning and Optimization for Medical Education and Decision Support 6.
- Deep Learning and Multimedia for Medical Education and Decision Support
- 7.
- Deep Learning and Traditional Methods for Medical Education and Decision Support.
- (source: Nielsen Book Data)
- Publisher's summary
-
This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today's problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation. .
(source: Nielsen Book Data)
Subjects
- Subjects
- Artificial intelligence > Medical applications.
- Machine learning.
- Decision support systems.
- Computational intelligence
- Image processing
- Machine learning
- Medical informatics
- Optical data processing
- Signal processing
- Speech processing systems
- Medical equipment & techniques.
- Computer vision.
- Imaging systems & technology.
- Artificial intelligence.
- Computers > Intelligence (AI) & Semantics.
- Medical > General.
- Computers > Computer Vision & Pattern Recognition.
- Technology & Engineering > Electronics > General.
- Technology & Engineering > Engineering (General).
Bibliographic information
- Publication date
- 2021
- Series
- Studies in Computational Intelligence ; v.909
- ISBN
- 9789811563256
- 981156325X
- 9811563241
- 9789811563249
- 9789811563263 (print)
- 9811563268
- 9789811563270 (print)
- 9811563276
- DOI
- 10.1007/978-981-15-6325-6
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