Multi‐modal Neuroimaging Based Dementia Risk Score for Early Detection of Future Risk of Dementia Onset for Alzheimer's Disease

This study underscores the potential of leveraging multi-modal deep learning models toward improving accuracy in AD prediction and tracking progression. Results demonstrated complementary strengths of MRI and PET. The reduced performance on pMCI prediction indicates room for improvement with further fine-tuning process, more advanced multi-modal fusion strategy, as well as the best modality (e.g. FDG-PET and tau-PET). Future plans involve multi-modal fusion at an early stage of the model and further evaluate model generalizability using independent datasets such as NACC data.