Advertisement

Machine Learning in Medicine - a Complete Overview

  • Ton J. Cleophas
  • Aeilko H. Zwinderman

Table of contents

  1. Front Matter
    Pages i-xxiv
  2. Cluster and Classification Models

    1. Front Matter
      Pages 1-1
    2. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 17-24
    3. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 25-29
    4. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 31-34
    5. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 35-46
    6. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 47-52
    7. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 53-60
    8. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 61-65
    9. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 67-70
    10. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 71-75
    11. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 77-79
    12. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 101-104
    13. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 105-110
  3. (Log) Linear Models

    1. Front Matter
      Pages 111-111
    2. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 131-135
    3. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 143-148
    4. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 149-153
    5. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 165-169
    6. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 171-174
    7. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 175-182
    8. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 183-187
    9. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 189-194
    10. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 195-201
    11. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 207-210
    12. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 211-217
    13. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 219-222
    14. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 223-227
    15. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 233-239
    16. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 241-244
    17. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 245-251
    18. Ton J. Cleophas, Aeilko H. Zwinderman
      Pages 261-264

About this book

Introduction

The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector. It was written as a training companion, and as a must-read, not only for physicians and students, but also for any one involved in the process and progress of health and health care. In eighty chapters eighty different machine learning methodologies are reviewed, in combination with data examples for self-assessment. Each chapter can be studied without the need to consult other chapters.

The amount of data stored in the world's databases doubles every 20 months, and clinicians, familiar with traditional statistical methods, are at a loss to analyze them. Traditional methods have, indeed, difficulty to identify outliers in large datasets, and to find patterns in big data and data with multiple exposure / outcome variables. In addition, analysis-rules for surveys and questionnaires, which are currently common methods of data collection, are, essentially, missing. Fortunately, the new discipline, machine learning, is able to cover all of these limitations.

So far medical professionals have been rather reluctant to use machine learning. Also, in the field of diagnosis making, few doctors may want a computer checking them, are interested in collaboration with a computer or with computer engineers. Adequate health and health care will, however, soon be impossible without proper data supervision from modern machine learning methodologies like cluster models, neural networks, and other data mining methodologies.

Each chapter starts with purposes and scientific questions. Then, step-by-step analyses, using data examples, are given. Finally, a paragraph with conclusion, and references to the corresponding sites of three introductory textbooks, previously written by the same authors, is given.

Keywords

Coputer science Data mining Machine learning SPSS statistical software various data mining software packages

Authors and affiliations

  • Ton J. Cleophas
    • 1
  • Aeilko H. Zwinderman
    • 2
  1. 1.Department Medicine Albert Schweitzer HospitalSliedrechtThe Netherlands
  2. 2.Academic Medical CenterDepartment Biostatistics and EpidemiologyAmsterdamThe Netherlands

Bibliographic information