A recent 2025 study led by Zhang et al. analyzed longitudinal data from China’s CHARLS to identify key predictors of depression in middle-aged and older individuals. By combining LSTM and CNN models, the study reveals that disability, life satisfaction, and ADL impairment are major influencers. This research exemplifies how digital technologies can enhance early detection strategies.
Q&A
- What does the study predict?
- How were machine learning models integrated?
- What are the main predictive features identified?