Advancing biomedical knowledge that is computable, connected, and worthy of trust.
Using health data, biomedical technologies, and informatics methods to make research faster, more rigorous, more reproducible, and more connected to care — helping establish clinical research informatics as a foundational discipline for modern biomedical discovery.
He coined and defined algorithmovigilance: the systematic monitoring of AI-driven health care for safety, effectiveness, equity, and performance over time. The goal is to make AI in medicine not only innovative, but observable, governable, and worthy of trust.
Building systems in which care, research, evidence, and improvement reinforce one another — so health systems learn continuously, responsibly, and at scale.
Transforming health data, biomedical evidence, and clinical expertise into structured, connected, machine-usable knowledge — governed for integrity so that people, institutions, and AI systems can rely on it.
For more than a decade, the closing keynote of the AMIA Informatics Summit — a curated tour of the year’s most notable clinical research informatics scholarship, with search strategy, bibliography, and slides for each year.
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