Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification
Author:
Funder
the Korean Fund for Regenerative Medicine (KFRM) grant
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-69090-3.pdf
Reference44 articles.
1. Rachner, T. D., Khosla, S. & Hofbauer, L. C. Osteoporosis: Now and the future. Lancet 377, 1276–1287 (2011).
2. Lane, N. E. Epidemiology, etiology, and diagnosis of osteoporosis. Am. J. Obstetr. Gynecol. 194, S3–S11. https://doi.org/10.1016/j.ajog.2005.08.047 (2006).
3. Anam, A. K. & Insogna, K. Update on osteoporosis screening and management. Med. Clin. North Am. 105, 1117–1134. https://doi.org/10.1016/j.mcna.2021.05.016 (2021).
4. Cummings, S. R. & Melton, L. J. Epidemiology and outcomes of osteoporotic fractures. Lancet 359, 1761–1767. https://doi.org/10.1016/s0140-6736(02)08657-9 (2002).
5. Siris, E. S. et al. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch. Intern. Med. 164, 1108–1112. https://doi.org/10.1001/archinte.164.10.1108 (2004).
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