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MMAP: Multimodal Missing-Aware Pretraining for Longitudinal Alzheimer's Prediction

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Clinical decision making heavily relies on predicting the disease progression trajectory by seeking to understand patient's health status which is characterised by multimodal medical data. AI holds great potential for learning useful representations from multimodal medical data to predict disease progression and aid clinical decision making. However, development of predictive AI models is constrained by missing modalities and incomplete tabular data frequently occurring in medical datasets. In addition, disease labels alone may only provide limited supervisory signals for learning representati

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