Skip to main content

Webinar Library

Democratizing AI for Cancer with Privacy Preserving Synthetic Data Generation for Cancer Case Identification

As part of the Department of Energy’s partnership with the National Cancer Institute, the Modeling Outcomes Using Surveillance Data and Scalable AI for Cancer (MOSSAIC) project aims to develop deep learning models to support near-real-time cancer surveillance at the population level. Through the NCI’s Surveillance, Epidemiology, and End Results (SEER) program, we deploy models for the automated coding of cancer cases across state and regional cancer registries throughout the United States.

AI Scientists for Biomedical Discoveries

In this talk, James Zou, PhD explores how generative AI agents can enable drug discovery and development. He introduces the Virtual Lab—a collaborative team of AI scientist agents conducting in silico research meetings to tackle open-ended R&D projects.