Predicting cognitive impairment in Parkinson's disease: a machine learning approach based on clinical and neuropsychological data.

ABSTRACT:

Background

Cognitive impairment is a common and disabling non-motor symptom of Parkinson's disease, markedly diminishing quality of life and elevating caregiver burden. Although considerable research has been conducted, the early prediction of cognitive impairment remains challenging owing to heterogeneous clinical presentations, variations in treatment adherence, and the inherent limitations in sensitivity of conventional biomarkers and cognitive assessment tools.

Methods and materials

A retrospective cohort study involving 514 Parkinson's disease patients who had complete baseline data and a minimum of 6 months of follow-up. Participants were randomly allocated into a training cohort (n = 359) and a test cohort (n = 155). Demographic, clinical, biochemical, a

SUBMITTER: Yang M 

PROVIDER: S-EPMC12757295 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature