Joshua Harvey, PhD Candidate, University of Exeter Medical School, Exeter, UK, discusses the findings of a machine learning study aiming to establish a model for predicting cognitive outcomes in patients with Parkinson’s disease (PD). Longitudinal data from newly diagnosed PD cases were used to investigate the best combination of baseline variables – clinical, biofluid, and genetic – to predict the occurrence of cognitive impairment and dementia conversion over an eight-year time frame. While the machine learning algorithms used differed in their predictive performance, the models incorporating clinical variables consistently performed best. Some improvement was seen when clinical, biofluid, and genetic markers were all included in one model. This interview took place at the Alzheimer’s Research UK (ARUK) Conference 2023 in Aberdeen, UK.
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