Back to Journals » Clinical Interventions in Aging » Volume 21 Artificial Intelligence for Osteoporosis Diagnosis, Risk Prediction and Therapy: Current Advances, Clinical Challenges, and Future Perspectives Authors Zhang Z, He Y , Mo Z, Zhang P, Tian Z, Huang L Received 5 March 2026 Accepted for publication 4 June 2026 Published 18 June 2026 Volume 2026:21 607232 DOI https://doi.org/10.2147/CIA.S607232 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 3 Editor who approved publication: Dr Maddalena Illario Zhaochen Zhang,1,* Yuxi He,2,* Zhanhao Mo,3,* Peng Zhang,4 Zhenya Tian,5 Lanfeng Huang1 1Department of Orthopedics, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 2Department of Ophthalmology, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 3Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 4Department of Radiology, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 5The First Norman Bethune Clinical Medical College, Jilin University, Changchun, Jilin, People’s Republic of China *These authors contributed equally to this work Correspondence: Lanfeng Huang, Department of Orthopedics, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China, Email [email protected] Abstract: Osteoporosis (OP) is a chronic systemic skeletal disorder that predominantly affects the elderly. It is characterized by an imbalance in bone homeostasis, reduced bone mass, microarchitectural deterioration of bone tissue, and increased bone fragility, ultimately leading to a higher risk of fractures and related complications. With the progression of global population aging, the prevalence of OP continues to rise, underscoring the importance of early diagnosis and timely intervention. However, the diagnosis and management of OP—particularly its early detection—remain limited by material constraints such as diagnostic equipment and by subjective factors including clinician experience, which hinder widespread screening. In recent years, artificial intelligence (AI)