Hidden Bibliographic Details
| Other authors / contributors: | Zwinderman, Aeilko H., author.
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| ISBN: | 9783030199180
3030199185
3030199177
9783030199173
9783030199197
3030199193
9783030199203
3030199207
9783030199173
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| Digital file characteristics: | text file PDF
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| Notes: | Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed September 18, 2019).
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| Summary: | Machine learning and big data is hot. It is, however, virtually unused in clinical trials. This is so, because randomization is applied to even out multiple variables. Modern medical computer files often involve hundreds of variables like genes and other laboratory values, and computationally intensive methods are required. This is the first publication of clinical trials that have been systematically analyzed with machine learning. In addition, all of the machine learning analyses were tested against traditional analyses. Step by step statistics for self-assessments are included. The authors conclude, that machine learning is often more informative, and provides better sensitivities of testing than traditional analytic methods do.
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| Other form: | Printed edition: 9783030199173
Printed edition: 9783030199197
Printed edition: 9783030199203
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| Standard no.: | 10.1007/978-3-030-19918-0
10.1007/978-3-030-19
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