Working Group Webinar Library

This talk shares insights from real-world use of text-based AI at the bedside—from opioid misuse screening via EHR notes to Ambient AI for automating documentation—highlighting both opportunities and risks, as well as approaches for evaluation and improvement.

In this session, Dr. Peterson and Dr. Ryu will discuss their journey building an LLM application at Mayo Clinic that scaled from an idea to thousands of active users. Attention to product design and AI safety were two key factors that enabled this success and will be the focus of the session.

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.

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.

This dynamic discussion will feature perspectives from academia, clinical practice, and industry, highlighting practical strategies for integrating AI solutions into healthcare settings. Panelists will share experiences, challenges, and lessons learned from implementation efforts, with a focus on governance, workflow integration, and impact assessment.