A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation

Abstract

The authors present a machine learning approach that combines baseline multimodal data to accurately predict individualised trajectories of future pathological tau accumulation at asymptomatic and mildly impaired stages of Alzheimer’s disease.