Application of Machine Learning to Identify Clinically Meaningful Risk Group for Osteoporosis in Individuals Under the Recommended Age for Dual-Energy X-Ray Absorptiometry-Reference-Cited by-同舟云学术

Application of Machine Learning to Identify Clinically Meaningful Risk Group for Osteoporosis in Individuals Under the Recommended Age for Dual-Energy X-Ray Absorptiometry

Published:2021-06-30 Issue:6 Volume:109 Page:645-655
ISSN:0171-967X
Container-title:Calcified Tissue International
language:en
Short-container-title:Calcif Tissue Int

Author:

Park Hyun Woo,Jung Hyojung,Back Kyoung Yeon,Choi Hyeon Ju,Ryu Kwang Sun,Cha Hyo Soung,Lee Eun Kyung,Hong A Ram^ORCID,Hwangbo Yul^ORCID

Funder

National Cancer Center

Publisher

Springer Science and Business Media LLC

Subject

Endocrinology,Orthopedics and Sports Medicine,Endocrinology, Diabetes and Metabolism

Link

https://link.springer.com/content/pdf/10.1007/s00223-021-00880-x.pdf

Reference41 articles.

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3. Ahn SH, Park SM, Park SY et al (2020) Osteoporosis and osteoporotic fracture fact sheet in Korea. J Bone Metab 27(4):281–290. https://doi.org/10.11005/jbm.2020.27.4.281

4. Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S, Lindsay R, National Osteoporosis F (2014) Clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int 25:2359–2381. https://doi.org/10.1007/s00198-014-2794-2

5. Obermeyer Z, Emanuel EJ (2016) Predicting the future—big data, machine learning, and clinical medicine. N Engl J Med 375:1216–1219. https://doi.org/10.1056/NEJMp1606181

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