Dr. Bazzaro, along with other collaborators, was part of a project, "FRANCIS: An AI-Driven Morphology-Based Platform for Enhanced Ovarian Cancer Prognostication and Treatment of Guidance" which was recommended for funding by the Department of Defense under the Ovarian Cancer Research Program. This is a 4-year, $1.4M project. It is designed to unlock rich, actionable biology from routine H&E pathology slides, using explainable AI to extract tumor, stromal, immune and collagen architectural features - bringing precision oncology within reach without costly or invasive assays.
Researchers from the Masonic Cancer Center, University of Minnesota in collaboration with Emory University and the Georgia Institute of Technology have developed a new artificial intelligence (AI) biomarker tool that may help predict how ovarian cancer patients will respond to treatment at the time of diagnosis. The findings were published in the British Journal of Cancer Reports
In a major scientific breakthrough, newly published research from an international consortium led by the University of Minnesota’s Masonic Cancer Center has the potential to transform the landscape of ovarian cancer treatment.
Researchers from the University of Minnesota have discovered that a protein associated with metabolism, and formerly recognized as a potential therapeutic target for ovarian cancer, may instead be associated with a better prognosis for women with this cancer.
The University of Minnesota proudly announces that Asumi Hoshino, a PhD student in the Molecular Pharmacology and Therapeutics (MPaT) Graduate Program, has been awarded both the prestigious Doctoral Dissertation Fellowship (DDF) and the esteemed Schmit-Steer Award.
Every year, the Masonic Cancer Center rounds up a list of their top accomplishments from across the cancer center, from research, to clinical trial enrollments, to outreach and engagement, and giving. Check out the top 20 accomplishments from 2024 by clicking the link below.
Dr. Bazzaro will be chairing a session called “From Pixel to Pathways: AI in the Identification of Cellular Features” at the upcoming American Society for Cell Biology 2026 which will be held in San Diego, CA on December 12-15, 2026.