AI Behavioral Health Project

Overview

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).

CERC

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

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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.

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Tracy Terada

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. 

 

Samira Daswani

Research Assistant

Samira is an entrepreneur working at the intersection of design, healthcare and technology. Using the power of human-centered design, she is tackling one of the most pressing

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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.

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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

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in quality improvement, population health, medical education, adolescent medicine and mental health. In addition to her role with HEA3RT, Dr. Sattler is the Program Director for the Stanford Primary Care Performance Enhancement Program (PC-PEP), a rapid-cycle quality improvement program that empowers front-line faculty and staff to tackle day-to-day operational problems. She is also the Quality Improvement Lead for both the Stanford Primary Care Faculty Practices and the Stanford School of Medicine Continuity of Care Clerkship.

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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

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at Stanford on the development and implementation of artificial intelligence technologies that improve the lives of patients, providers and health systems. Her expertise lies in healthcare quality improvement, complex problem solving, facilitating cross discipline collaboration, and design thinking. Margaret holds a bachelor’s degree in finance and risk management, a master’s in business administration with a specialization in healthcare management from Baylor University, Robbins Institute for Health Policy and Leadership, and a Lean Six-Sigma black belt certification.

 

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Grace Eunhae Hong

Research Associate

Grace Hong was born and raised in Illinois and graduated from Stanford University in 2019 with a B.A. in Economics.

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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.

 

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Department of Computer Science

Dr. Ehsan Adeli

Scientist, Stanford AI Lab, Stanford Vision and Learning, Computer Science Department
Clinical Assistant Professor, Department of Psychiatry and Behavioral Sciences, Stanford School of Medicine

Ketan Jay Agrawal

Graduate Student, Computer Science

Ketan is a member of PAC, where his research interests include human pose estimation, knowledge representation, and graph structures.

Ruta Joshi

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.

Neha Srivastha

Undergraduate Student