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Louis Faust, Ph.D., is a data scientist and digital health researcher who leverages wearable health sensors to enhance healthcare delivery models and improve patient outcomes. His research applies novel machine-learning methodologies to the physiological and behavioral signals captured from these devices to construct interpretable and reproducible measures. With applications in clinical trials and remote monitoring, Dr. Faust's work uses these data streams to quantify, evaluate and predict patient health and well-being.
Wearable health sensors provide opportunities for passive data collection outside the hospital walls. Dr. Faust's research leverages this innovation by employing data science and machine-learning techniques on information collected through these devices for applications across the healthcare domain. Through the development of a machine-learning model to identify seizures in patients with epilepsy, Dr. Faust's research aims to use wrist-worn devices as a noninvasive alternative to implantable EEGs for seizure monitoring. Additionally, Dr. Faust's research seeks to minimize patient burden through reduced in-person visits and need to self-report data. Central to this is integrating objective measures from health sensors into clinical workflows, such as quantifying physical function in people receiving chemotherapy to assess treatment tolerance.
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