Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region
Issued Date
2026-01-01
Resource Type
ISSN
0937941X
eISSN
14332965
Scopus ID
2-s2.0-105039413303
Pubmed ID
42142131
Journal Title
Osteoporosis International
Rights Holder(s)
SCOPUS
Bibliographic Citation
Osteoporosis International (2026)
Suggested Citation
Huang C.F., Fang W.H., Chen K.H., Lin S.Y., Ho C.J., Hwang J.S., Tai T.W., Liu Y.F., Shih C.A., Chen J.F., Tu S.T., Chan D.C., Yang R.S., Fu S.H., Chen H.Y., Tsai K.S., Cheng T.T., Chen F.P., Hung W.C., Chang Y.F., Han D.S., Chandran M., Bin A.S., Lee J.K., Yeap S.S., Chung Y.S., Kim K.K., Ebeling P.R., Jaisamrarn U., Pandey D., Ferrari S., Yang T.H., Charatcharoenwitthaya N., Taguchi A., Lekamwasam S., Van Nguyen T., Lewiecki E.M., Saag K.G., Tsai C.C., Marín F., Mori S., Hwang K.R., Li-Yu J., Carey J.J., Kendler D., Cheung C.L., Huang H.K., Kuptniratsaikul V., Chan W.P., Chan S.P., Ho-Pham L.T., Hew F.L., Shi H., Rhee Y., McCloskey E., Tanaka S., Hans D., Kanis J.A., Chen C.H., Wu C.H. Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region. Osteoporosis International (2026). doi:10.1007/s00198-026-08067-6 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/116952
Title
Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region
Author(s)
Huang C.F.
Fang W.H.
Chen K.H.
Lin S.Y.
Ho C.J.
Hwang J.S.
Tai T.W.
Liu Y.F.
Shih C.A.
Chen J.F.
Tu S.T.
Chan D.C.
Yang R.S.
Fu S.H.
Chen H.Y.
Tsai K.S.
Cheng T.T.
Chen F.P.
Hung W.C.
Chang Y.F.
Han D.S.
Chandran M.
Bin A.S.
Lee J.K.
Yeap S.S.
Chung Y.S.
Kim K.K.
Ebeling P.R.
Jaisamrarn U.
Pandey D.
Ferrari S.
Yang T.H.
Charatcharoenwitthaya N.
Taguchi A.
Lekamwasam S.
Van Nguyen T.
Lewiecki E.M.
Saag K.G.
Tsai C.C.
Marín F.
Mori S.
Hwang K.R.
Li-Yu J.
Carey J.J.
Kendler D.
Cheung C.L.
Huang H.K.
Kuptniratsaikul V.
Chan W.P.
Chan S.P.
Ho-Pham L.T.
Hew F.L.
Shi H.
Rhee Y.
McCloskey E.
Tanaka S.
Hans D.
Kanis J.A.
Chen C.H.
Wu C.H.
Fang W.H.
Chen K.H.
Lin S.Y.
Ho C.J.
Hwang J.S.
Tai T.W.
Liu Y.F.
Shih C.A.
Chen J.F.
Tu S.T.
Chan D.C.
Yang R.S.
Fu S.H.
Chen H.Y.
Tsai K.S.
Cheng T.T.
Chen F.P.
Hung W.C.
Chang Y.F.
Han D.S.
Chandran M.
Bin A.S.
Lee J.K.
Yeap S.S.
Chung Y.S.
Kim K.K.
Ebeling P.R.
Jaisamrarn U.
Pandey D.
Ferrari S.
Yang T.H.
Charatcharoenwitthaya N.
Taguchi A.
Lekamwasam S.
Van Nguyen T.
Lewiecki E.M.
Saag K.G.
Tsai C.C.
Marín F.
Mori S.
Hwang K.R.
Li-Yu J.
Carey J.J.
Kendler D.
Cheung C.L.
Huang H.K.
Kuptniratsaikul V.
Chan W.P.
Chan S.P.
Ho-Pham L.T.
Hew F.L.
Shi H.
Rhee Y.
McCloskey E.
Tanaka S.
Hans D.
Kanis J.A.
Chen C.H.
Wu C.H.
Author's Affiliation
The University of British Columbia
Monash University
The University of Hong Kong
The University of Sheffield
The University of Alabama at Birmingham
Universiti Malaya
University of Technology Sydney
Mahidol University
Chulalongkorn University
Chang Gung Memorial Hospital
Centre Hospitalier Universitaire Vaudois
National Yang-Ming University Taiwan
Hôpitaux Universitaires de Genève
National Taiwan University Hospital
Chang Gung University
University of Galway
National Sun Yat-Sen University
Kaohsiung Medical University
National Taiwan University College of Medicine
Chang Gung University College of Medicine
Duke-NUS Medical School
Singapore General Hospital
National Cheng Kung University College of Medicine
Shanghai General Hospital
I-Shou University
Ajou University School of Medicine
Veterans General Hospital-Taichung Taiwan
Severance Hospital
Kaohsiung Medical University College of Medicine
Chaoyang University of Technology
The University of Tokyo Hospital
Hualien Tzu Chi Hospital
Seoul Metropolitan Government - Seoul National University Borame Medical Center
National Pingtung University of Science and Technology
Chi Mei Medical Center
Taipei Municipal Wan-Fang Hospital
Changhua Christian Hospital
KK Women's And Children's Hospital
National Defense University Taiwan
University of Ruhuna
Faculty of Medicine, Thammasat University
Konyang University, College of Medicine
Ajou University Hospital
Seirei Hamamatsu General Hospital
Matsumoto Dental University
University of Santo Tomas Hospital
Subang Jaya Medical Centre
New Mexico Clinical Research and Osteoporosis Center
National Academy of Medical Sciences
Pham Ngoc Thach University of Medicine
Beacon Hospital
Quironsalud University Hospital
Tam Anh Research Institute
Far Eastern Polyclinic of Far Eastern Medical Foundation
Real-World Study and Application Centre
Monash University
The University of Hong Kong
The University of Sheffield
The University of Alabama at Birmingham
Universiti Malaya
University of Technology Sydney
Mahidol University
Chulalongkorn University
Chang Gung Memorial Hospital
Centre Hospitalier Universitaire Vaudois
National Yang-Ming University Taiwan
Hôpitaux Universitaires de Genève
National Taiwan University Hospital
Chang Gung University
University of Galway
National Sun Yat-Sen University
Kaohsiung Medical University
National Taiwan University College of Medicine
Chang Gung University College of Medicine
Duke-NUS Medical School
Singapore General Hospital
National Cheng Kung University College of Medicine
Shanghai General Hospital
I-Shou University
Ajou University School of Medicine
Veterans General Hospital-Taichung Taiwan
Severance Hospital
Kaohsiung Medical University College of Medicine
Chaoyang University of Technology
The University of Tokyo Hospital
Hualien Tzu Chi Hospital
Seoul Metropolitan Government - Seoul National University Borame Medical Center
National Pingtung University of Science and Technology
Chi Mei Medical Center
Taipei Municipal Wan-Fang Hospital
Changhua Christian Hospital
KK Women's And Children's Hospital
National Defense University Taiwan
University of Ruhuna
Faculty of Medicine, Thammasat University
Konyang University, College of Medicine
Ajou University Hospital
Seirei Hamamatsu General Hospital
Matsumoto Dental University
University of Santo Tomas Hospital
Subang Jaya Medical Centre
New Mexico Clinical Research and Osteoporosis Center
National Academy of Medical Sciences
Pham Ngoc Thach University of Medicine
Beacon Hospital
Quironsalud University Hospital
Tam Anh Research Institute
Far Eastern Polyclinic of Far Eastern Medical Foundation
Real-World Study and Application Centre
Corresponding Author(s)
Other Contributor(s)
Abstract
Summary: Osteoporosis is a major and growing health concern in the Asia-Pacific region, y et it remains widely underdiagnosed and undertreated due to limited access to dual-energy X-ray absorptiometry (DXA) in many areas. Artificial intelligence (AI) offers new opportunities to improve osteoporosis screening and management, but unvalidated tools pose risks of inconsistent care. This consensus was developed to provide regionally harmonized guidance on the safe, effective, and equitable use of AI in osteoporosis care. Purpose: The aim of this work was to establish expert consensus recommendations on the role of AI in osteoporosis screening and management in the Asia-Pacific region. Key objectives were to define appropriate applications of AI (e.g., imaging-based bone assessment and fracture risk prediction) and specify minimum standards for validation and reporting, addressing region-specific implementation challenges and ensuring that AI use aligns with clinical guidelines and ethical principles. Methods: This consensus was developed through multidisciplinary collaboration among experts across the Asia-Pacific region. Each participant reviewed draft statements, contributed feedback during virtual meetings, and provided insights based on clinical experience and current evidence. Consensus was reached iteratively until full agreement was achieved for all statements. The process integrated global best practices and regional adaptations, drawing from peer-reviewed studies, international AI guidelines, and local fracture registry data. The final recommendations emphasize the validation, transparency, and ethical implementation of AI within regional healthcare systems, ensuring compatibility with local regulations. Ultimately, twelve consensus statements were established to guide the responsible use of AI for osteoporosis screening and management in the Asia-Pacific region. Results: The panel produced 12 consensus statements covering the role of AI as an adjunct for opportunistic osteoporosis screening rather than a diagnostic tool, requirements for imaging quality and AI model transparency, standards for validation and performance reporting, integration of AI with clinical risk stratification, demonstration of clinical utility in real-world settings, adherence to data protection laws and ethical AI principles, training of clinicians in AI use, strategies for implementation and monitoring (including post-market surveillance and feedback loops), and recognition of technical, clinical, and equity limitations of AI. All 12 statements give extensive recommendations for using AI to improve osteoporosis management while ensuring patient safety, accuracy, and equity. Conclusion: This first Asia-Pacific consensus on AI in osteoporosis concludes that AI, when appropriately validated and implemented, can help bridge the osteoporosis care gap by identifying high-risk patients who would otherwise remain undiagnosed, thus facilitating earlier intervention. It emphasizes that AI should complement—not replace—standard diagnostic methods and clinical judgment. The guidance emphasizes validation, transparency, and ethical oversight to facilitate early intervention while minimizing risks associated with unvalidated or premature AI adoption.