AI helps accelerate breast cancer diagnosis for high-risk women
Peer-Reviewed Publication
Updates every hour. Last Updated: 31-Oct-2026 20:16 ET (1-Nov-2026 00:16 GMT/UTC)
Women with abnormal mammograms often have to wait for weeks to find out whether they have breast cancer.
Now, researchers at UC San Francisco and UC Berkeley have found a way to help reduce the wait and the worry by using AI to quickly identify those who are most likely to have the disease. By triaging these patients, the AI-guided workflow takes women with abnormal scans through the diagnostic process — from imaging to evaluation and sometimes even biopsy — in a single day.
Since its founding more than a century ago, the Boyce Thompson Institute (BTI) has been a place where bold scientific ideas take root. From advancing plant science and training future researchers, to fostering entrepreneurship and innovation, BTI has long served as a launchpad for scientific discovery. That legacy continues today with innovation extending far beyond the walls of the Institute — and across the globe.
One of the latest examples is PrecizionIQ, an India-based health technology startup co-founded by BTI alumnus Pedro Rodrigues, a former postdoctoral researcher in the lab of Frank Schroeder at BTI. The company is developing novel, non-invasive diagnostics for fetal chromosomal abnormalities, with a mission to make early prenatal testing more accurate, affordable and accessible.
A UC Irvine-led study analyzed 3,511 cancer patients across six UC medical centers to examine infection-related side effects to antibody-drug conjugates, or ADCs.
Researchers found some ADC therapies were linked to dangerously low infection-fighting white blood cell counts and related complications, including hospitalization.
Led by pharmacy professor Alexandre Chan, the study highlights the need for closer monitoring and supportive care as targeted cancer therapies become more widely used.