Incorporating longitudinal variability in prediction models: A comparison of machine learning and logistic regression in a cohort study with long follow-up
Machine Learning methods did not outperform logistic regression. Nonetheless, incorporating variability in longitudinal predictors enhances prediction, especially with expected changes in predictors, e.g., ageing populations.
Authors
- Martijn W. Heymans (ORCID: https://orcid.org/0000-0002-3889-0921)
- Almar A. L. Kok (ORCID: https://orcid.org/0000-0001-6398-2484)
- Jos W. R. Twisk (ORCID: https://orcid.org/0000-0001-9617-1020)
- Lichelle Groot (ORCID: https://orcid.org/0000-0002-3333-2023)
Institutions
- Amsterdam Neuroscience (NL)
- Public Health Service of Amsterdam (NL)
- Amsterdam University Medical Centers (NL)
Publication Details
- Journal
- Annals of Epidemiology
- Published
- 2025-07-26
- DOI
- https://doi.org/10.1016/j.annepidem.2025.07.060
- Citations
- 3
- Primary Topic
- Mental Health Research Topics
- Type
- article
- Field-Weighted Citation Impact
- 6.35