LongMoE: Longitudinal Multimodal Learning via Trajectory-Aware Mixture-of-Experts

In three linesLongMoE introduces a Mixture-of-Experts framework for longitudinal multimodal clinical learning. It jointly addresses modality missingness and temporal disease trajectory dynamics through context-aware imputation, attentional tokenization, trajectory-aware encoding, and context-conditioned Sparse MoE routing. Evaluated on ADNI, OASIS-3, MIMIC-IV datasets.

Summary generated by Claude — human-verified