AI has the potential to fundamentally transform healthcare — from better clinical interventions to deeper understanding of human health. Given the systemic health disparities that exist already in the healthcare system, it is essential that machine learning methods serve the entire patient population. Our group leverages novel health data resources and innovative computational techniques to revolutionize machine learning for equitable healthcare. We derive high-impact insights across patient risk stratification, treatment guidelines, clinical-decision making, and scientific discovery.
Through pioneering advancements at the intersection of AI and medicine, we aim to elevate healthcare to serve diverse populations more precisely, more justly, and more comprehensively.
Led by Prof. Irene Chen, the CHEN Lab is an interdiscplinary research group in Computational Precision Health and Electrical Engineering and Computer Science at UC Berkeley and UC San Francisco. Our interdisciplinary team unites clinicians, data scientists, and experts across fields to unravel health insights and develop equitable clinical interventions. We collaborate widely, from computer scientists to anthropologists, pursuing impact across critical care, diabetes, maternal health, and beyond.
Our research focuses on three core questions:
- How can we design clinical interventions to treat underserved groups?
- How can we discover health insights of heterogeneous populations?
- How can we ensure that algorithms don’t magnify existing bias?