Flexible Multimodal Fusion of Neuroimaging Modalities for Alzheimer's Disease Progression Prediction

PerMod-MoE, with its addition of independent, modality-specific routers in the sparse mixture-of-experts layer, improves performance on AD progression prediction when neuroimaging modality availability is severely limited during inference. PerMod-MoE offers a novel approach to effectively leverage available neuroimaging data for more accurate AD progression prediction by clinical providers.