Machine learning–based survival models for predicting rehospitalization of older hip fracture patients: a retrospective cohort study
The effect of feature selection on model performance highlights the need for comprehensive variable selection and model evaluation strategies to improve predictive accuracy.
Authors
- Jaewon Oh (ORCID: https://orcid.org/0000-0002-4585-1488)
- Yonghan Cha (ORCID: https://orcid.org/0000-0002-7616-6694)
- Jae‐Hyun Kim (ORCID: https://orcid.org/0000-0001-6387-191X)
- Eun‐Cheol Park (ORCID: https://orcid.org/0000-0002-2306-5398)
- Seung Hoon Kim (ORCID: https://orcid.org/0000-0002-7704-6213)
Institutions
- Dartmouth Institute for Health Policy and Clinical Practice (US)
- Eulji University (KR)
- Soonchunhyang University (KR)
- Dankook University (KR)
Publication Details
- Journal
- BMC Musculoskeletal Disorders
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1186/s12891-025-08710-z
- Citations
- 2
- Primary Topic
- Hip and Femur Fractures
- Type
- article
- Field-Weighted Citation Impact
- 4.01
Funders
- Soonchunhyang University
- Ministry of Health and Welfare