Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods
Abstract Background Clinical prediction models (CPMs) predict the risk of health outcomes for individual patients. The majority of existing CPMs only harness cross-sectional patient information. Incorporating repeated measurements, such as those stored in electronic health records, into CPMs may pro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-07-01
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| Series: | Diagnostic and Prognostic Research |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s41512-020-00078-z |