Development and evaluation of a machine learning model for osteoporosis risk prediction in Korean women
This study found that an XGBoost model can be utilized to classify osteoporosis in Korean women. Age at menopause is a significant factor in osteoporosis risk, followed by arthritis, physical activities, hypertension, and education level.
Authors
- Seunghyeon Hwang (ORCID: https://orcid.org/0000-0002-1038-519X)
- Minkyung Je (ORCID: https://orcid.org/0000-0001-6093-1569)
- Suwon Lee (ORCID: https://orcid.org/0000-0003-2603-1385)
- Yoona Kim (ORCID: https://orcid.org/0000-0002-3924-8543)
Institutions
- Gyeongsang National University (KR)
Publication Details
- Journal
- BMC Women s Health
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1186/s12905-025-03669-4
- Citations
- 8
- Primary Topic
- Bone health and osteoporosis research
- Type
- article
- Field-Weighted Citation Impact
- 13.77
Funders
- National Research Foundation of Korea