Risk Prediction Workshop Series on Algorithmic Fairness: Workshop 2
Registration is now open for the second session of the Risk Prediction Workshop Series, taking place during the Spring 2026 semester.
This series, Algorithmic Fairness: Concepts, Evaluation, and Real-World Case Studies, explores fairness considerations in statistical, machine learning, and AI algorithms used in clinical and biomedical applications. Across the series, we cover foundational concepts, emerging methodological advances, and real-world PSOM case studies, including evaluations of fairness in lung cancer screening.
February 26 session overview:
This session examines a key weakness of standard fairness metrics, such as equal opportunity, and discusses how overlooking it can lead to incorrect conclusions about equity in model performance.
Session details:
- Time: 12:00–1:30 p.m.
- Location: 3600 Civic Center Boulevard (CCB), Room 05C-031
- Map: https://maps.google.com/?q=3600+Civic+Center+Blvd,+Philadelphia,+PA+19104Links to an external site.
- Capacity: Space is limited to 25; lunch will be provided
- Co-sponsored by: CCEB and ACC
Finding the room:
Take the elevator to the 5th floor, turn right when exiting the elevator, go through the double doors, and the room will be on your left.
Upcoming sessions (same time and location):
- March 26, 2026: A review of causal fairness evaluation (tentative)
- April 23, 2026: Professor Summer Han (Stanford University) on lung cancer screening and prediction modeling, including fairness considerations
If you plan to attend the February 26 session, please register using the link below. Advance registration is required due to space limitations.