CPH in the News
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Researchers Discover New Way to Detect Sudden Cardiac Death Risk
Ziad Obermeyer, MD, CPH PhD student, Alex Schubert, and collaborators featured in Berkeley News for their latest Nature publication, using more than 440,000 EKGs from Sweden to train an artificial intelligence model to analyze the spikes and waveforms produced by the heart’s electrical currents.
HACHI for Clinicians and Data Scientists
Jean Feng, PhD, and collaborators featured in UCSF News and Nature have developed HACHI, a new model for developing tools that pairs AI’s ability to rapidly analyze medical records with the expertise of clinicians.
Using Wearables Data in the Clinic
Ida Sim, MD, PhD, featured in STAT News, sharing her perspective on the value of wearables data and the challenges of integration in the clinic.
Reducing Breast Cancer Screening Time for High-Risk Women
Adam Yala, PhD, and Maggie Chung, MD, featured in UCSF News for their latest Nature publication, showing that the model created by Yala reduced the wait time for a diagnostic evaluation from several weeks to about an hour.
The OpenEvidence Episode: Dr. Travis Zack on the Future of Clinical Evidence
Listen to NEJM AI Grand Rounds featuring Travis Zack, MD, PhD, discussing that reasoning—not just correctness—defines good care, and that evidence must be contextual, accessible, and usable.
Sylvia Cheng and Romain Pirracchio, MD, MPH, PhD, Share Findings at AMIA Informatics Conference in Denver
Sylvia and Romain built a reinforcement learning model using real-world data from UCSF to answer a critical question: how can we design an optimal treatment policy that both signals and treats elevated perioperative blood glucose to reduce life-threatening postoperative outcomes?
