SynthesisOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2021
Application of artificial intelligence in diagnosis of osteoporosis using medical images: a systematic review and meta-analysis.
Synthesis in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 4 syntheses or guidelines pooled it, 37 citations in OpenAlex.
- Accuracy of artificial intelligence in detecting tumor bone metastases: a systematic review and meta-analysis.BMC cancer · 2025Pooled it
- Diagnostic accuracy of artificial intelligence models in detecting osteoporosis using dental images: a systematic review and meta-analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025Pooled it
- Diagnostic accuracy of chest X-ray and CT using artificial intelligence for osteoporosis: systematic review and meta-analysis.Journal of bone and mineral metabolism · 2024Pooled it
- Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis.BMC medical informatics and decision making · 2024Pooled it
- Application of a Remotely Controlled Artificial Intelligence Analgesic Pump Device in Painless Treatment of Children.Contrast media & molecular imaging · 2022Trial
- Artificial Intelligence for Osteoporosis Diagnosis, Risk Prediction and Therapy: Current Advances, Clinical Challenges, and Future Perspectives.Clinical interventions in aging · 2026Review
- Relationship Between Lumbar Spine Hounsfield Unit Values and Bone Mineral Density in Patients With Osteoarthritis Undergoing Total Hip Arthroplasty.Arthroplasty today · 2025Article
- The Early Detection of Osteoporosis Through the Measurement of Hard Palate Thickness (HPT) Using Dental Cone Beam Computed Tomography (CBCT): A New Indicator for Osteoporosis?Diagnostics (Basel, Switzerland) · 2025Article
- Artificial intelligence for predicting the risk of bone fragility fractures in osteoporosis.European radiology experimental · 2025Review
- Diagnostic Accuracy of Deep Learning for the Prediction of Osteoporosis Using Plain X-rays: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2024Review
- New Horizons: Artificial Intelligence Tools for Managing Osteoporosis.The Journal of clinical endocrinology and metabolism · 2023Article
- Detection of sarcopenia using deep learning-based artificial intelligence body part measure system (AIBMS).Frontiers in physiology · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Artificial intelligence (AI) is a potentially reliable assistant in the diagnosis of osteoporosis. This meta-analysis aims to assess the diagnostic accuracy of the AI-based systems using medical images. We searched PubMed and Web of Science from inception to June 15, 2020, for eligible articles that applied AI approaches to diagnosing osteoporosis using medical images. Quality and bias of the included studies were evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The main outcome was the sensitivity and specificity of the performance of the AI-based systems. The data analysis utilized the R Foundation packages of "meta" for univariate analysis and Stata for bivariate analysis. Random effects model was utilized. Seven studies with 3186 patients were included in the meta-analysis. The overall risk of bias of the included studies was assessed as low. The pooled sensitivity was 0.96 (95% CI 0.93-1.00), and the pooled specificity was 0.95 (95% CI 0.91-0.99). However, high heterogeneity was found in this meta-analysis. The results supported that the AI-based systems had good accuracy in diagnosing osteoporosis. However, the high risk of bias in patient selection and high heterogeneity in the meta-analysis made the conclusion less convincing. The application of AI-based systems in osteoporosis diagnosis needs to be further confirmed by more prospective studies in multi-centers including more random samples from complete patient types.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.