Pioneering the integration of artificial intelligence into clinical practice to transform patient care, advance medical knowledge, and ensure safe deployment of AI in healthcare.
Professor & Chair, Department of Biomedical Informatics
Editor-in-Chief, NEJM AI
What I'm working on now →Our work spans three interconnected domains that are reshaping the future of medicine
Developing AI tools that enhance diagnosis, treatment, and clinical decision-making. From early detection of growth disorders to diagnosis of rare diseases.
An international initiative studying whose values are embedded in clinical AI. Over 1,000 clinicians enrolled across three continents, measuring alignment between AI models and human decision-makers.
Empowering patients with granular control over their health data through innovative protocols like PING and Guardian Angel for secure, auditable data sharing.
Key contributions over 30+ years of research
NEJM (2021) - Dataset shift has already impacted healthcare.
Identifies several components of the challenge for AI deployment and regulation in healthcare.
NEJM AI (2024) - Finding the right comparators for clinical AI
Grounding evaluations with respect to the practice we have rather than the clinical care we wish we had.
Pearson (2023) - Conversational lay guide to impact of generative AI on biomedicine.
Early book on LLM transformation of healthcare, research and consumer experiences.
MIT/LCS TR-389 (1987) - Pioneering temporal reasoning across healthcare data types
Applied constraint propagation and context switching techniques.
IJCAI (1993) - Monitoring noisy and sparse clinical data streams.
J Pediatrics (1997) - Prospective Trial
Our lab brings together graduate students, postdocs, and visitors from diverse backgrounds to tackle medicine's most pressing challenges through computational innovation.
"The skill we most treasure and work to nurture in our lab is the ability to ask interesting, important, and potentially answerable questions."