Our work covers a broad range of aims centered on the development and integration of artificial intelligence (AI) technologies that solve important, practical problems for patients, providers and health systems. 

We work with clinical, operational, and technical teams to advance the development of clinically relevant models, leveraging quality improvement, implementation science, design thinking, and traditional research methods.

Director's Message

Read a message from HEA3RT's Executive Director Dr. Steven Lin and learn about the mission and vision of our program 

Work With Us

Learn about ways to engage with HEA3RT, whether you're a prospective partner from industry, academia, or the non-profit world

Projects

Explore our projects studying the implementation of AI technologies in healthcare to support patients, providers, and health systems

Recent News & Publications

Meeting the Moment: Addressing Barriers and Facilitating Clinical Adoption of AI in Medical Diagnosis

NAM Perspectives, September 2022

A new NAM Perspectives discussion paper acknowledges that AI-based diagnostic decision support tools have broad potential to revolutionize the field of medical diagnostics by supplementing the ability of clinicians to make informed decisions for their patients, as well as potentially reduce cognitive burden and alleviate clinician burnout. However, these tools may fail to achieve wide uptake if there is insufficient clinical acceptance. This paper outlines a framework for considering and overcoming barriers to adoption centered around the reason, means, method, and desire to use these tools while addressing intersecting issues of equity.

Integrating AI into Depression and Anxiety Screening to Support Equity and Inclusion in Behavioral Healthcare

November 2022

As demonstrated in our previous proof-of-concept study that leveraged our existing depression screening protocol that was recently awarded the 2021 Malinda Mitchell Award for Quality, an AI-based approach to mental health diagnosis and monitoring can detect subtle behavioral changes in patients with depression and anxiety. In our upcoming study, in collaboration with CERC and supported by a DOM Chair Diversity Investigator Award, we will expand the scope of the research to include a larger, more diverse population to develop an AI tool that effectively identifies individuals at risk of depression and/or anxiety across age, socioeconomic, and ethnic groups.