Progress in machine learning-assisted medical imaging for osteoarthritis and osteoporosis diagnosis: a narrative review

Abstract

AI-assisted imaging is reshaping OA and OP assessment by enabling earlier detection and more objective longitudinal monitoring. However, clinical translation is hindered by limited interpretability of many DL models and substantial data heterogeneity. Future research should prioritize standardized multicenter datasets and explainable AI frameworks. Prospective clinical studies and rigorous external validation are needed to bridge the gap between research and practice and to advance personalized musculoskeletal care.

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