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Machine Learning in Medicine - Cookbook (Paperback, 2014) Loot Price: R1,762
Discovery Miles 17 620
Machine Learning in Medicine - Cookbook (Paperback, 2014): Ton J. Cleophas, Aeilko H. Zwinderman

Machine Learning in Medicine - Cookbook (Paperback, 2014)

Ton J. Cleophas, Aeilko H. Zwinderman

Series: SpringerBriefs in Statistics

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Loot Price R1,762 Discovery Miles 17 620 | Repayment Terms: R165 pm x 12*

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The amount of data in medical databases doubles every 20 months, and physicians are at a loss to analyze them. Also, traditional methods of data analysis have difficulty to identify outliers and patterns in big data and data with multiple exposure / outcome variables and analysis-rules for surveys and questionnaires, currently common methods of data collection, are, essentially, missing.

Obviously, it is time that medical and health professionals mastered their reluctance to use machine learning and the current 100 page cookbook should be helpful to that aim. It covers in a condensed form the subjects reviewed in the 750 page three volume textbook by the same authors, entitled Machine Learning in Medicine I-III (ed. by Springer, Heidelberg, Germany, 2013) and was written as a hand-hold presentation and must-read publication. It was written not only to investigators and students in the fields, but also to jaded clinicians new to the methods and lacking time to read the entire textbooks.

General purposes and scientific questions of the methods are only briefly mentioned, but full attention is given to the technical details. The two authors, a statistician and current president of the International Association of Biostatistics and a clinician and past-president of the American College of Angiology, provide plenty of step-by-step analyses from their own research and data files for self-assessment are available at extras.springer.com.

From their experience the authors demonstrate that machine learning performs sometimes better than traditional statistics does. Machine learning may have little options for adjusting confounding and interaction, but you can add propensity scores and interaction variables to almost any machine learning method."

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: SpringerBriefs in Statistics
Release date: 2014
First published: 2014
Authors: Ton J. Cleophas • Aeilko H. Zwinderman
Dimensions: 235 x 155 x 8mm (L x W x T)
Format: Paperback
Pages: 137
Edition: 2014
ISBN-13: 978-3-319-04180-3
Categories: Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 3-319-04180-0
Barcode: 9783319041803

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