Ensemble Deep Learning Models for Brain Connectivity in Alzheimer's Disease Diagnosis via Different Perspectives

The results highlight the potential of multimodal ensemble networks in neuroimaging-based AD diagnosis. By integrating population-level relationships and robust feature representations, BrainEnsNet and PopEnsNet set a foundation for advancing diagnostic accuracy. Future research could incorporate longitudinal data and additional imaging modalities to enhance clinical utility and generalizability.