Machine learning in medicine / by Ton J. Cleophas, Aeilko H. Zwinderman ; with help from Eugene P. Cleophas, Henny I. Cleophas-Allers.
"Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and discriminant analysis. It is currently mainly the domain of computer scientists, and is already co...
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| Main Authors: | , |
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| Format: | Ebook |
| Language: | English |
| Published: |
Dordrecht :
Springer,
2013.
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| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | "Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and discriminant analysis. It is currently mainly the domain of computer scientists, and is already commonly used in social sciences, marketing research, operational research and applied sciences. It is virtually unused in clinical research. This is probably due to the traditional belief of clinicians in clinical trials where multiple variables are equally balanced by the randomization process and are not further taken into account. In contrast, modern computer data files often involve hundreds of variables like genes and other laboratory values, and computationally intensive methods are required. This book was written as a hand-hold presentation accessible to clinicians, and as a must-read publication for those new to the methods."--Publisher's website. |
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| Physical Description: | 1 online resource (270 pages) |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9400758243 9789400758247 |