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Machine Learning in Medicine
Cleophas, Ton J.; Zwinderman, Aeilko H.
€ 67.75
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Description for Machine Learning in Medicine
Hardcover.
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 ... Read more
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 ... Read more
Product Details
Format
Hardback
Publication date
2013
Publisher
Springer Netherlands
Condition
New
Number of Pages
265
Place of Publication
Dordrecht, Netherlands
ISBN
9789400758230
SKU
V9789400758230
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Machine Learning in Medicine
From the reviews: “This novel book on machine learning in medicine deals with statistical methods for analyzing complex data involving multiple variables. … The intended audience includes physicians, clinical researchers, physicians in training, statisticians, and medical students, as well as master’s and doctoral students in epidemiology and biostatistics. … The language is simple and the chapters are well organized. ... Read more