5 researchers · 6 publications
Develop algorithms that use non-invasive physiological data to diagnose disease presence and severity and predict treatment efficacy. Key projects include predicting vagus nerve stimulation treatment response for drug-resistant epilepsy patients, and using machine learning on autonomic nervous system biomarkers to detect and quantify PTSD presence and severity from physiological signatures. This work uses heart rate variability and other non-invasive measures to build parsimonious diagnostic and prognostic models.