Article

A Novel Dynamic Graph Architecture for Staging Parkinson’s Disease Progression Using Cerebrospinal Fluids Longitudinal Profiles

2026-03-08

Abstract excerpt

<title>Abstract</title> <p>Dynamic graph learning methods typically capture local structural information and short-range temporal dependencies at each time step. In this work, we introduce a dynamic graph learning architecture that generates time-step embeddings capturing both local structural context and progression-trajectory patterns for each node across an entire longitudinal sequence. The framework clusters...

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Literature Corpus work: 919749b5-cb96-5ea3-acc8-933d769126a8
DOI: 10.21203/rs.3.rs-9034342/v1

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