Development and validation of a machine learning-based risk prediction model for sarcopenia in community hospital patients: a retrospective cohort study

In conclusion, ML models show substantial potential for clinical application in identifying sarcopenia risk, thereby supporting early intervention strategies. This approach enhances detection capabilities and provides a practical tool for individualized treatment planning in community-based elderly care. Future research should integrate additional biomarkers and environmental factors to further improve model accuracy and facilitate integration into clinical workflows.