AI Behavioral Health Project
Currently patients are screened for depression and anxiety through standardized surveys. These surveys can be difficult for a person to fill out and often need to be done more than once. Research studies have found that audio and visual changes can be detected by computer algorithms to help identify symptoms of depression and anxiety. We are conducting a study to see if we can construct reliable artificial intelligence (AI) algorithms to detect depression and/or anxiety through recorded video interviews.
Observational, open label study that will recruit 100 patients to collect sufficient audio and video responses within the a primary care setting to build an AI-platform to correlate behavioral health conditions (depression and anxiety) with visual and audio cues.
Patients will be asked to complete the PHQ-9 and the GAD-7 questionnaires and speak into a camera that captures audio and video data. Patients will be asked a series of questions in a private room.
A preliminary evaluation of the algorithm will result in a directional estimates of whether or not we should proceed to the next phase of development of the algorithm (and collect more data).
Dr. Nirav Shah
CERC Senior Scholar
Dr. Nirav Shah is a Senior Scholar at Stanford University’s Clinical Excellence Research Center. He is a leader in patient safety and quality, innovation and digital health, and the strategies required to
transistion to lower-cost, patient-centered health care. Board-certified in Internal Medicine, Dr. Shah is a graduate of Harvard College and Yale School of Medicine, and is an elected member of the National Academy of Medicine.
Dr. Shah serves as an independent director for STERIS plc, as an Advisor to Deerfield Management, and as a trustee of The John A. Hartford Foundation. He is a Senior Fellow of the Institute for Healthcare Improvement (IHI), and helps set the health priorities for the United States as a member of the HHS Secretary's Advisory Committee on National Health Promotion and Disease Prevention Objectives for 2030. Previously, he served as senior vice president and Chief Operating Officer for clinical operations for Kaiser Permanente in Southern California, and as Commissioner of the New York State Department of Health.
Research Operations Manager
Tracy is a 15+ year adminstrative veteran for the Stanford School of Medicine. She started at the Lane Medical Library and is currently with the Clinical Excellence Research Center.
problems of our generation - mental health, isolation and burnout. Together with a group of talented individuals, Samira built a product that helps individuals better manage their emotional wellbeing.
She has been a part of 2 different technology startups and a consultant at McKinsey & Company. She brings a unique blend of design, operations and strategy to all her projects. She earned a Master's degree in Engineering, Design at Stanford University, a bachelor’s degree in biological engineering and art history from MIT and Wellesley College respectively.
As an avid scuba diver and a red belt in Taekwondo, Samira spends her time exploring beautiful places.
Stanford Healthcare AI Applied Research Team (HEA3RT)
Dr. Amelia Louise Sattler
Clinical Assistant Professor, Associate Director
Dr. Sattler is the Associate Director of HEA3RT. She joined Stanford Family Medicine in 2013, and is an ebullient family physician with special interests
Margaret Smith MBA
Director of Operations
Margaret Smith is the Director of Operations of HEA3RT where she works with industry collaborators, and clinical and operational leaders
Grace Eunhae Hong
Grace Hong was born and raised in Illinois and graduated from Stanford University in 2019 with a B.A. in Economics.
Grace works with the Stanford Healthcare AI Applied Research Team (HEA3RT) to study the implementation of AI technologies in healthcare settings and has a special interest in better understanding how innovations in health technology can be used to improve access to healthcare and remedy health disparities.
Department of Computer Science
Graduate Student, Computer Science
Ruta is a masters student at PAC. Her research interests include computer vision and robotics for healthcare situations and emergency response.