Integrating dynamic nomogram and machine learning for personalized disability prediction in elderly cardiometabolic multimorbidity: routine blood markers and mental health
This study utilizes CHARLS data to develop a dynamic nomogram and machine learning models demonstrating that depression is a dominant predictor of disability in elderly patients with cardiometabolic multimorbidity, while routine blood markers provide significant risk stratification and the disability risk plateaus after three concurrent chronic diseases.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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