Ensemble-learning approach improves fracture prediction using genomic and phenotypic data
The ensemble learning approach significantly improved fracture prediction accuracy and model performance compared to individual ML. Integrating genomic and phenotypic data via the SL approach represents a promising advancement for personalized osteoporosis management.
Authors
- Qing Wu (ORCID: https://orcid.org/0000-0003-4679-8903)
- Jong-Yun Jung (ORCID: https://orcid.org/0000-0002-9258-5397)
Institutions
- The Ohio State University (US)
Publication Details
- Journal
- Osteoporosis International
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1007/s00198-025-07437-w
- Citations
- 6
- Primary Topic
- dental development and anomalies
- Type
- article
- Field-Weighted Citation Impact
- 4.84
Funders
- National Institute on Aging
- National Institute on Minority Health and Health Disparities