Predicting Geriatric Rehabilitation Stays of ≤4 Weeks After Hip Fracture Surgery: Machine Learning Approach Using Physical Activity and Patient Data
This study developed several ML models to predict a geriatric rehabilitation stay of ≤4 weeks in a skilled nursing home for older patients after hip fracture surgery. Among these models, the SVM proved to be highly accurate in its predictions with an accuracy of 0.95 (95% CI 0.85-1.00), precision of 0.91 (95% CI 0.71-1.00), recall of 1.00 (95% CI 1.00-1.00), F<sub>1</sub>-score of 0.95 (95% CI 0.83-1.00), and AUC of 0.97 (95% CI 0.88-1.00).
Authors
- Frank J. Wouda (ORCID: https://orcid.org/0000-0002-4401-4434)
- Sanne Krakers (ORCID: https://orcid.org/0009-0003-2499-0694)
- Miriam MR Vollenbroek-Hutten
- Dieuwke van Dartel
- Up&Go After a Hip Fracture Group
- Johannes H Hegeman
Institutions
- Medisch Spectrum Twente (NL)
- Ziekenhuis Groep Twente (NL)
- University of Twente (NL)
Publication Details
- Journal
- JMIR Rehabilitation and Assistive Technologies
- Published
- 2026-02-23
- DOI
- https://doi.org/10.2196/79331
- Primary Topic
- Hip and Femur Fractures
- Type
- article
- Field-Weighted Citation Impact
- 0.00