Conference item
An unsupervised learning model for pattern recognition in routinely collected healthcare data
- Abstract:
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This study examines a large routinely collected healthcare database containing patient-level self-reported outcomes following knee replacement surgery. A model based on unsupervised machine learning methods, including k-means and hierarchical clustering, is proposed to detect patterns of pain experienced by patients and to derive subgroups of patients with different outcomes based on their pain characteristics. Results showed the presence of between two and four different sub-groups of patien...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Accepted manuscript, pdf, 705.3KB)
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- Publisher copy:
- 10.5220/0006535602660273
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Authors
Funding
National Institute for Health Research
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Bibliographic Details
- Publisher:
- Scitepress Publisher's website
- Journal:
- 11th International Conference on Health Informatics (HEALTHINF 2018) Journal website
- Host title:
- 11th International Conference on Health Informatics (Healthinf 2018)
- Publication date:
- 2018-02-01
- Acceptance date:
- 2017-10-30
- DOI:
- Source identifiers:
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742155
Item Description
- Keywords:
- Pubs id:
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pubs:742155
- UUID:
-
uuid:b61e58b5-6b06-41ff-8325-c51d3db107d4
- Local pid:
- pubs:742155
- Deposit date:
- 2017-11-01
Terms of use
- Copyright holder:
- Science and Technology Publications, Lda
- Copyright date:
- 2018
- Notes:
- Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
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