Implementation of a dynamic model updating pipeline provides a systematic process for maintaining performance of prediction models
Implementing a dynamic updating pipeline will help guard against model performance degradation while ensuring that the updating process is principled and data-driven.
Authors
- Kamaryn Tanner (ORCID: https://orcid.org/0000-0001-6613-7833)
- Karla Díaz-Ordaz (ORCID: https://orcid.org/0000-0003-3155-1561)
- Ruth H. Keogh (ORCID: https://orcid.org/0000-0001-6504-3253)
Institutions
- University of London (GB)
- London School of Hygiene & Tropical Medicine (GB)
- University College London (GB)
Publication Details
- Journal
- Journal of Clinical Epidemiology
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1016/j.jclinepi.2024.111531
- Citations
- 1
- Primary Topic
- Fault Detection and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.33
Funders
- Wellcome Trust
- UK Research and Innovation
- Royal Society
- Cystic Fibrosis Trust