The Academy of Translational Medicine (ATM) is excited to announce the first session of our interdisciplinary workshop series, ATM Learns.
In this first session, Dr. Xiaoxiao Li will discuss Generative AI in Healthcare: Advances, Pitfalls, and Path Forward.
Abstract:
Artificial intelligence is transforming healthcare, offering powerful tools for biomedical data analysis and clinical decision-making. This talk will provide an overview of recent advances in applying state-of-the-art AI methods, including transformer-based foundation models, to medical image analysis. While these models have shown promise, significant challenges remain such as bias, limited interpretability, and difficulty adapting to real-world clinical contexts. Dr. Li will discuss strategies to address these challenges with a focus on improving fairness, robustness, and clinical utility. The talk will also examine the ongoing debate over the use of general-purpose foundation models compared with specialized medical models, considering their cost, scalability, and impact. Dr. Li will conclude by outlining a path toward developing trustworthy AI systems that can meaningfully advance patient care.
About Dr. Li:
Dr. Xiaoxiao Li is an assistant professor in the Department of Electrical and Computer Engineering at the University of British Columbia, a faculty member at the Vector Institute, and a visiting research scholar at Google. Dr. Li is recognized as a Canada Research Chair (Tier II) in Responsible AI and a CIFAR AI Chair. Their research focuses on the intersection of AI and healthcare, the theory and techniques for artificial general intelligence (AGI), and AI trustworthiness. Dr. Li’s work aims to develop the next generation of responsible AI algorithms and systems.
Date: October 15, 2025
Time: 3:00 to 4:00 PM PST
Location: Zoom