ArticleArchives of osteoporosis2025
The Role of ChatGPT in osteoporosis management: a comparative analysis with clinical expertise.
Article in Archives of osteoporosis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Densitometric gains do not uniformly translate into clinical and psychosocial recovery: a 12-month multidimensional analysis of romosozumab therapy in postmenopausal osteoporosis.BMC musculoskeletal disorders · 2026Article
- Assessing Readability and DISCERN Quality of Osteoporosis Education Materials Generated by ChatGPT and Deepseek for Diverse Health Literacy Levels: A Cross-Sectional Study.Health science reports · 2026Article
- Artificial Intelligence in Rheumatology: From Algorithms to Clinical Impact in Osteoporosis and Chronic Inflammatory Rheumatic Diseases.Journal of clinical medicine · 2026Article
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Authors and funding
2 authors.
Funding
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Abstract
This study evaluates the role of ChatGPT in osteoporosis management, demonstrating 91% diagnostic accuracy and significantly faster response times compared to clinicians. The findings highlight the potential for artificial intelligence (AI) to revolutionize clinical decision-making while emphasizing the critical need for professional oversight to ensure patient safety and comprehensive care.
objectiveOsteoporosis is a progressive skeletal disease that is characterized by increased bone fragility and an increased risk of fracture. Early diagnosis and effective treatment can significantly reduce healthcare costs; however, limited access to clinical expertise represents a significant challenge to patient care. This study evaluates the diagnostic and treatment recommendations provided by natural language processing (NLP)-based AI models for osteoporosis management and compares them with those of healthcare professionals.
methodsA multicenter, cross-sectional study was conducted with the creation of 100 real scenarios from 206 patients with a diagnosis of osteoporosis. The data pertaining to bone mineral density (BMD) and the clinical parameters were subjected to analysis using ChatGPT-4.0. Thereafter, the recommendations proffered by this software were compared to those of five independent physiatrists. A statistical validation of the model's accuracy was conducted through the use of categorical distribution analysis.
resultsChatGPT exhibited a high degree of diagnostic accuracy, with 91% of responses being entirely accurate. It provided recommendations for both pharmacological and non-pharmacological interventions that were consistent with current clinical guidelines. Nevertheless, 8% of the responses were reported as incomplete. Furthermore, ChatGPT was able to produce diagnoses and treatment recommendations at a significantly faster rate than clinicians, while the mean answer time is 5.4 ± 2.45 min in clinicians and 2.3 ± 0.76 min in ChatGPT (p < 0.001).
conclusionThese findings highlight the potential of AI tools like ChatGPT to improve efficiency in clinical decision-making while underscoring the necessity of collaboration with healthcare professionals to guarantee comprehensive patient care.
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Registered trials
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