Journal article
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
- Abstract:
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OBJECTIVE: To compare performance of logistic regression (LR) with machine learning (ML) for clinical prediction modeling. STUDY DESIGN AND SETTING: We conducted a Medline literature search (1/2016 to 8/2017), and extracted comparisons between LR and ML models for binary outcomes. RESULTS: We included 71 out of 927 studies. The median sample size was 1250 (range 72-3,994,872), with 19 predictors considered (range 5-563) and 8 events per predictor (range 0.3-6,697). The most common ML methods ...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 1.4MB, Terms of use)
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- Publisher copy:
- 10.1016/j.jclinepi.2019.02.004
Authors
Bibliographic Details
- Publisher:
- Elsevier
- Journal:
- Journal of Clinical Epidemiology More from this journal
- Volume:
- 110
- Pages:
- 12-22
- Publication date:
- 2019-02-11
- Acceptance date:
- 2019-02-05
- DOI:
- ISSN:
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1878-5921
Item Description
- Language:
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English
- Keywords:
- Pubs id:
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pubs:973554
- UUID:
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uuid:4167c905-5171-4fc7-b157-ff36d56a73db
- Local pid:
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pubs:973554
- Source identifiers:
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973554
- Deposit date:
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2019-02-15
Terms of use
- Copyright holder:
- Elsevier Inc
- Copyright date:
- 2019
- Rights statement:
- © 2019 Elsevier Inc. All rights reserved.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.jclinepi.2019.02.004
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