DINMC: A Deep Learning Framework for Interpretable Normative Model Construction and Pathological Brain Alteration Detection (opens in new tab)

Background and Objective: Normative modeling is a key tool for understanding brain alterations in neurodegenerative diseases, such as cerebellar-type multiple system atrophy. However, existing methods lack interpretability and fail to capture clinically meaningful pathological changes. This study presents DINMC, a Deep Interpretable Normative Model Construction framework, which combines autoencoder-based learning with statistical hypothesis testing to better capture and interpret disease-spec...