AI algorithms for accurate prediction of osteoporotic fractures in patients with diabetes: an up-to-date review

• Published in: Journal of orthopaedic surgery and research Vol. 18; no. 1; pp. 956 - 11
• Main Authors: Li, Zeting, Zhao, Wen, Lin, Xiahong, Li, Fangping
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 12.12.2023; BioMed Central; BMC
• Subjects: Algorithms; Artificial Intelligence; Bone Density; Bone turnover; Care and treatment; Chronic obstructive pulmonary disease; Denosumab; Diabetes; Diabetes Mellitus; Diabetics; Fracture prediction; Fractures; Hip Fractures - epidemiology; Hip joint; Humans; Kidney diseases; Medical research; Medicine, Experimental; Metabolism; Mortality; Orthopedics; Osteoporosis; Osteoporosis - complications; Osteoporosis - diagnosis; Osteoporotic fracture; Osteoporotic Fractures - diagnosis; Osteoporotic Fractures - epidemiology; Osteoporotic Fractures - etiology; Predictions; Review; Rheumatoid arthritis; Risk Assessment; Risk Factors; Type 2 diabetes; United Kingdom > UK; China; Diabetes; Fracture prediction; Artificial intelligence; Osteoporotic fracture

Osteoporotic fractures impose a substantial burden on patients with diabetes due to their unique characteristics in bone metabolism, limiting the efficacy of conventional fracture prediction tools. Artificial intelligence (AI) algorithms have shown great promise in predicting osteoporotic fractures....