ArticleJournal of bone metabolism2023
Effect of Artificial Intelligence or Machine Learning on Prediction of Hip Fracture Risk: Systematic Review.
Article in Journal of bone metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in osteoporosis screening and fracture risk prediction among aging populations: a bibliometric evidence map.Frontiers in endocrinology · 2026Pooled it
- When demography challenges policy: the rising burden of proximal femur fractures as a role model and driver for geriatric trauma care in Germany.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2026Article
- An explainable machine learning approach to predict fragility fractures and the identification of important features.Scientific reports · 2026Article
- The neuro-skeletal crosstalk: Mechanisms, clinical implications, and smart material interventions.Journal of orthopaedic translation · 2026Review
- Accuracy of artificial intelligence in prediction of osteoporotic fractures in comparison with dual-energy X-ray absorptiometry and the Fracture Risk Assessment Tool: A systematic review.World journal of orthopedics · 2025Article
- Frontal plane mechanical leg alignment estimation from knee x-rays using deep learning.Osteoarthritis and cartilage open · 2025Article
- Federated multimodal AI for precision-equitable diabetes care.Frontiers in digital health · 2025Review
- Development and validation of a predictive model for vertebral fracture risk in osteoporosis patients.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundDual energy X-ray absorptiometry (DXA) is a preferred modality for screening or diagnosis of osteoporosis and can predict the risk of hip fracture. However, the DXA test is difficult to implement easily in some developing countries, and fractures have been observed before patients underwent DXA. The purpose of this systematic review is to search for studies that predict the risk of hip fracture using artificial intelligence (AI) or machine learning, organize the results of each study, and analyze the usefulness of this technology.
methodsThe PubMed, OVID Medline, Cochrane Collaboration Library, Web of Science, EMBASE, and AHRQ databases were searched including "hip fractures" AND "artificial intelligence".
resultsA total of 7 studies are included in this study. The total number of subjects included in the 7 studies was 330,099. There were 3 studies that included only women, and 4 studies included both men and women. One study conducted AI training after 1:1 matching between fractured and non-fractured patients. The area under the curve of AI prediction model for hip fracture risk was 0.39 to 0.96. The accuracy of AI prediction model for hip fracture risk was 70.26% to 90%.
conclusionsWe believe that predicting the risk of hip fracture by the AI model will help select patients with high fracture risk among osteoporosis patients. However, to apply the AI model to the prediction of hip fracture risk in clinical situations, it is necessary to identify the characteristics of the dataset and AI model and use it after performing appropriate validation.
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