Technical brief presents methods for using machine learning to predict outcomes in Parkinson's disease cohorts, highlighting open science benefits.
This document summarizes the theoretical rationale and methods for “A Machine Learning Approach to Derive Biology Driven Parkinson’s Disease Subtypes and Predict Longitudinal Clinical Outcomes Across Multiple Cohorts.” This project was funded by the Michael J. Fox Foundation in 2023 through the Data Driven Subtyping and Stratification Program, Grant ID MJFF 023158. This technical brief is intended to help researchers understand and use the resources produced by this project in an open science context.
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Santos et al. (2026) studied this question.
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