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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.
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Machine Learning in Medicine
2013, Springer Netherlands, Imprint: Springer
electronic resource /
in English
9400758243 9789400758247
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September 16, 2024 | Edited by MARC Bot | import existing book |
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July 5, 2019 | Created by MARC Bot | Imported from Internet Archive item record |