- Abstract:
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Purpose of Review Machine learning methods are increasingly used in health data mining. We describe current unsupervised learning methods for phenotyping and discovery and illustrate their application for detecting features and sub-groups related to drug use within a population.
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's Version
- Files:
-
-
(pdf, 1.3mb)
-
- Publisher copy:
- 10.1007/s40471-019-00211-7
-
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- Publisher:
- Springer Nature Publisher's website
- Journal:
- Current Epidemiology Reports Journal website
- Volume:
- 6
- Issue:
- 3
- Pages:
- 364-372
- Publication date:
- 2019-07-27
- Acceptance date:
- 2019-07-15
- DOI:
- EISSN:
-
2196-2995
- Pubs id:
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pubs:1046112
- URN:
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uri:11841c7f-71ff-486f-af35-e996050a6c03
- UUID:
-
uuid:11841c7f-71ff-486f-af35-e996050a6c03
- Local pid:
- pubs:1046112
- Language:
- English
- Keywords:
- Copyright holder:
- Khalid and Prieto-Alhambra
- Copyright date:
- 2019
- Notes:
- © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
Journal article
Machine learning for feature selection and cluster analysis in drug utilisation research
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