Article

Early Prediction of Parkinson’s Disease Progression by Integrating Research Cohort and Real-World Data Using Knowledge-Anchored Graph Learning

2026-07-09

Abstract excerpt

Parkinson’s disease (PD) progression is highly heterogeneous. Deeply phenotyped longitudinal research cohorts have enabled characterization of PD progression trajectories. Early prediction of these progression patterns can help us better understand patient disease conditions and manage appropriately. However, the sample sizes of these cohorts are typically too small to build robust early predictors, and usually it...

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Literature Corpus work: b44f6c5f-84aa-5ba8-afbc-1ed19dfc75f6
DOI: 10.64898/2026.07.07.26357483

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