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.
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.