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Lancet Diabetes Endocrinol., Jun 25 2024, S2213-8587(24)00153-0 | https://doi.org/10.1016/S2213-8587(24)00153-0 The potential role for artificial intelligence in fracture risk prediction

Namki Hong MD ^a,b, Danielle E Whittier PhD ^c, Prof Claus-C Glüer Dr rer nat ^d, Prof William D Leslie MD ^e

^aDepartment of Internal Medicine, Endocrine Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea

^bInstitute for Innovation in Digital Healthcare, Yonsei University Health System, Seoul, Korea

^cMcCaig Institute for Bone and Joint Health and Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

^dSection Biomedical Imaging, Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany

^eDepartment of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada

Correspondence to: Dr Namki Hong

Abstract

Osteoporotic fractures are a major health challenge in older adults. Despite the availability of safe and effective therapies for osteoporosis, these therapies are underused in individuals at high risk for fracture, calling for better case-finding and fracture risk assessment strategies. Artificial intelligence (AI) and machine learning (ML) hold promise for enhancing identification of individuals at high risk for fracture by distilling useful features from high-dimensional data derived from medical records, imaging, and wearable devices. AI-ML could enable automated opportunistic screening for vertebral fractures and osteoporosis, home-based monitoring and intervention targeting lifestyle factors, and integration of multimodal features to leverage fracture prediction, ultimately aiding improved fracture risk assessment and individualised treatment. Optimism must be balanced with consideration for the explainability of AI-ML models, biases (including information inequity in numerically under-represented populations), model limitations, and net clinical benefit and workload impact. Clinical integration of AI-ML algorithms has the potential to transform osteoporosis management, offering a more personalised approach to reduce the burden of osteoporotic fractures.

논문정보

형식Review Paper
게재일2024년 06월 (BRIC 등록일 2024-07-01)
연구진국내(교신)+국외 연구진
분야 의약학 > 응용의학

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