Machine Learning in Medicine

Authors: Cleophas, Ton J., Zwinderman, Aeilko H.

  • Electronic health records of modern health facilities, are increasingly complex and systematic assessment of these records is virtually impossible without special computationally intensive methods
  • Clinicians and other health professionals are not familiar with these methods, and this book is the first publication that systematically reviews such methods, particularly, for this audience
  • The book is written as a hand-hold presentation also accessible to non-mathematicians, and as a must-read publication for those new to the methods
  • The book includes step by step data analyses in SPSS, and can, therefore, also be used as a cookbook-like guide for those starting with the novel methodologies
see more benefits

Buy this book

eBook $69.99
price for USA (gross)
  • ISBN 978-94-007-5824-7
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $89.95
price for USA
  • ISBN 978-94-007-5823-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $89.95
price for USA
  • ISBN 978-94-007-9363-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

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.

Reviews

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. This will be an excellent resource for a quick review of machine learning in medicine, particularly in genetic research, clinical trials, and adverse drug surveillance.” (Parthiv Amin, Doody’s Book Reviews, September, 2013)

Table of contents (20 chapters)

  • Introduction to Machine Learning

    Cleophas, Ton J. (et al.)

    Pages 1-15

  • Logistic Regression for Health Profiling

    Cleophas, Ton J. (et al.)

    Pages 17-24

  • Optimal Scaling: Discretization

    Cleophas, Ton J. (et al.)

    Pages 25-38

  • Optimal Scaling: Regularization Including Ridge, Lasso, and Elastic Net Regression

    Cleophas, Ton J. (et al.)

    Pages 39-53

  • Partial Correlations

    Cleophas, Ton J. (et al.)

    Pages 55-64

Buy this book

eBook $69.99
price for USA (gross)
  • ISBN 978-94-007-5824-7
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $89.95
price for USA
  • ISBN 978-94-007-5823-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $89.95
price for USA
  • ISBN 978-94-007-9363-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Machine Learning in Medicine
Authors
Copyright
2013
Publisher
Springer Netherlands
Copyright Holder
Springer Science+Business Media Dordrecht
eBook ISBN
978-94-007-5824-7
DOI
10.1007/978-94-007-5824-7
Hardcover ISBN
978-94-007-5823-0
Softcover ISBN
978-94-007-9363-7
Edition Number
1
Number of Pages
XV, 265
Number of Illustrations and Tables
44 b/w illustrations
Topics