Hernandez-Boussard and Colleagues Find that SSRIs Reduce the Effectiveness of Hydrocodone and Codeine

Research led by BMIR's Tina Hernandez-Boussard, colleague Ian Carroll and grad student Arjun Parthipan found that patients on SSRIs such as Zoloft, Paxil and Prozac who were prescribed prodrug opoids such as hydrocodone or codeine experienced more post-surgery pain than patients not on SSRIs. Hernandez-Boussard's team built a machine-learning algorithm that predicts how a patient will respond to different types of opoids. 

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Read the Scope article


Gevaert and Lucence Dx Team Up to Apply AI to Liver Cancer Diagnosis and Treatment

BMIR’s Olivier Gevaert and Lucence Diagnostics have teamed up to develop artificial intelligence algorithms for improving diagnosis and treatment of liver cancer with the goal of combining imaging and molecular data from liver cancer patients into smarter software tools that help physicians make better treatment decisions.

Blood Test May Help Predict Severity of Dengue

BMIR’s Purvesh Khatri and colleague, Shirit Einav, identified 20 genes that can predict an individual’s likelihood of developing a severe form of dengue fever with about 80 percent accuracy.  Using their newly identified set of genes as a foundation, Khatri and Einav aim to identify predictive biomarkers that can help doctors reliably gauge the likelihood of severe dengue the likelihood of severe dengue in patients who are newly symptomatic and use that information to provide more accurate care to help guide therapeutic clinical studies and, in the future, to guide treatment decisions.

How should an algorithm generate recommendations for patient care?

Dr. Jonathan Chen and his colleagues are working to answer the question, "How should an algorithm generate recommendations for patient care?" This question was tackled as the latest step in Dr. Chen’s quest to build OrderRex, a tool that will mine data from electronic health records to inform medical decisions.

Explore BMIR

At BMIR, we develop computatiional methods for biomedical discovery that influence medical decisions.

Learn more about the cutting-edge ways we are advancing technology and biomedicine to improve human health.

Our state of the art research advances patient care by improving semantic technology, biostatistics, and the modeling of biomedical systems. Read more about our research labs.

Join us for our weekly research talks featuring world-renowned scientists, faculty, staff, and students.

BMIR Colloquia and Research in Progress talks occur on Thursdays from 12-1 PM during the academic year in Medical School Office Building room X275, 1265 Welch Road, Stanford, CA. See schedule.  

Notable Projects and Services

CEDAR is making data submission smarter and faster, so biomedical researchers and analysts create and use better metadata.


Diagnostics - Infectious Diseases

EteRNA, an online puzzle, enlists video gamers to try to design a sensor module that could make diagnosing TB as easy as taking a home pregnancy test.

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The NCBO manages a repository of all the world’s publicly available biomedical ontologies and terminologies—now more than 390 in number.

Green Button

Green button: the promise of personalizing medical practice guidelines in real time

Protégé is the most widely used ontology-development system in the world.


CoINcIDE, is a novel methodological framework for the discovery of patient subtypes across multiple datasets that requires no between dataset transformations.

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