Developing a machine learning-based predictive model for depression risk in patients with cardiovascular diseases - PubMed
5 hours ago
- #Cardiovascular Diseases
- #Machine Learning
- #Depression Risk
- Study aimed to develop a machine learning-based predictive model for depression risk in patients with cardiovascular diseases (CVD).
- Data from the China Health and Retirement Longitudinal Study (CHARLS) was used, with 2020 wave for training/testing and 2018 wave for validation.
- Eight machine learning models were evaluated, with AdaBoost showing superior performance.
- Key predictors of depression risk included life satisfaction, instrumental activities of daily living (IADL), sleep time, and self-rated health.
- The model may aid in early identification of high-risk individuals for depression in CVD patients.