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Machine Learning in Medicine

  • Ton J. Cleophas
  • Aeilko H. Zwinderman

Table of contents

  1. Front Matter
    Pages i-xv
  2. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 1-15
  3. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 17-24
  4. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 25-38
  5. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 55-64
  6. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 65-77
  7. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 79-86
  8. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 87-98
  9. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 99-111
  10. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 113-126
  11. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 127-143
  12. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 145-156
  13. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 157-166
  14. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 167-181
  15. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 183-195
  16. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 197-213
  17. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 215-224
  18. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 225-240
  19. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 241-253
  20. Ton J. Cleophas, Aeilko H. Zwinderman
    Pages 255-257
  21. Back Matter
    Pages 259-265

About this book

Introduction

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.

Keywords

cluster analysis data mining discriminant analysis factor analysis machine learning

Authors and affiliations

  • Ton J. Cleophas
    • 1
  • Aeilko H. Zwinderman
    • 2
  1. 1.SliedrechtNetherlands
  2. 2., Dept. Epidemiology and BiostatisticsAcademic Medical CenterAmsterdamNetherlands

Bibliographic information