Deep learning with ensemble-based hybrid AI model for bipolar and unipolar depression detection using demographic and behavioral based on time-series data

This work introduces a robust and interpretable framework for depression classification using synthetic multimodal data. While not clinically validated, the model serves as a methodological foundation for future research with real-world datasets.