We empower individuals with the collective experience of the many,
combining human and artificial intelligence approaches to medicine
that will deliver better care than what either can do alone.
About Us
Our Mission
Our research group seeks to empower individuals with the collective experience of the many, combining human and artificial intelligence approaches to deliver better care than either can do alone.
Tapping into real-world clinical data like electronic medical records with machine learning and data analytics will reveal the community's latent knowledge in a reproducible form. By delivering this back as clinical decision support, we aim to uniquely close the loop on a continuously learning health system.
The practice of modern medicine is faced with an explosive growth in biomedical knowledge with thousands of medical and surgical procedures, diagnostic tests, pharmaceutical drugs, and recognized disease states, where we routinely face a combinatorial explosion of possible medical decisions.
Informatics and computational approaches are the only credible approach to systematically address challenges in modern healthcare.
What We Do
Discover and distribute the latent knowledge embedded in health data.
Improve systems for clinical decision support by developing data-driven algorithms and user interfaces.
Infer patient context from electronic information in order to anticipate what a physician needs without the physician having to ask for it.
Define benchmarks to systematically evaluate the safety and efficacy of medical AI systems.
Train (and retrain) the next generation of an
AI-enabled healthcare workforce
Generated automated medical consultations, because no one benefits from a patient sitting on a waiting list!
Empower everyone in healthcare to practice to the top of their license.
The Team behind
HealthRex Lab
We conduct research, implement groundbreaking projects, and create innovative tools to reach new heights in medical data analysis and diagnostics.
Learn more about our team of postdoctoral professionals, fellows, and students making valuable contributions to biomedical informatics and related fields.
