Adnan and colleagues evaluated machine learning models’ ability to screen for Parkinson’s disease using self-recorded smile videos. 2. The models achieved high sensitivity and specificity among ...

Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...

The pipeline illustrates how EEG signals are processed for Parkinson's disease detection. Key features are extracted from brainwave data and transformed into images or movie representations. These are ...

In a major step forward for Parkinson’s care, researchers have used machine learning and UK Biobank data to predict who is most at risk of developing Parkinson’s disease dementia (PDD), highlighting ...