Development of a machine learning-based predictive model for osteoporosis risk and its application in clinical decision support

Abstract

The osteoporosis prediction model developed in this study achieved quantitative risk estimation and interpretable outputs using a limited set of features, providing a feasible technical approach for early screening of osteoporosis. Future work should focus on external validation and recalibration in multicenter populations to further evaluate and optimize the model's predictive performance and clinical applicability.

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