Systematic review of machine‑learning methods applied to remote monitoring for predicting disease outcomes, focused on methodological performance rather than biological mechanisms.

Improving remote monitoring and ML-derived digital biomarkers can help Parkinson’s trial design and outcome measurement but the paper offers limited direct insight for therapeutic targets or mechanistic discovery.