AI-Enabled Parkinson’s Disease Screening Using Smile Videos

We developed an AI-based screening framework that detects Parkinson’s disease from brief smile videos captured on a smartphone or webcam, demonstrating high accuracy and broad applicability, including in diverse population samples.

• Collected one of the largest annotated smile–video datasets to date, involving participants with and without PD from multiple settings.
• Extracted facial landmarks and motion features indicative of hypomimia (reduced facial expressivity), a hallmark PD motor symptom.
• Trained and validated machine learning models achieving ≈88% accuracy for distinguishing PD from non-PD using only smile videos.
• Demonstrated generalizability in external validation cohorts, including clinical and international datasets.
• Showed the approach is scalable and accessible, enabling remote, low-cost initial screening that could complement traditional clinical evaluations and improve early detection access.