Deep learning-based patient stratification for prognostic enrichment of clinical dementia trials.

ABSTRACT: Dementia probably due to Alzheimer's disease is a progressive condition that manifests in cognitive decline and impairs patients' daily life. Affected patients show great heterogeneity in their symptomatic progression, which hampers the identification of efficacious treatments in clinical trials. Using artificial intelligence approaches to enable clinical enrichment trials serves a promising avenue to identify treatments. In this work, we used a deep learning method to cluster the multivariate disease trajectories of 283 early dementia patients along cognitive and functional scores. Two distinct subgroups were identified that separated patients into 'slow' and 'fast' progressing individuals. These subgroups were externally validated and independently replicated in a dementia cohort compris

SUBMITTER: Birkenbihl C 

PROVIDER: S-EPMC11660909 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature