Review summarizes AI innovations for osteoporosis diagnosis and therapy, indicating clinical necessities and challenges.
Key Points
This review aims to summarize the applications of artificial intelligence in diagnosing and managing osteoporosis, while addressing methodological challenges.
Review of AI applications in osteoporosis across various medical domains.
Assessment of current studies focusing on diagnosis, risk prediction, and therapeutic interventions using AI.
Identification of key limitations in existing research and the need for standardized practices.
AI can enhance diagnostic accuracy and efficiency in osteoporosis management, reducing the time for musculoskeletal measurements significantly.
Challenges such as data imbalance and selection bias are prevalent in current AI studies on osteoporosis.
Insufficient external validation of AI models highlights the need for further collaborative research and methodological standardization.