TL;DR
- Fairness & Medical Imaging Tutorial at MICCAI 2025 (South Korea)
- Date: TBC
- Location: TBC
Scope
As AI transforms healthcare, ensuring fairness in medical imaging is crucial to prevent health disparities. This tutorial provides a comprehensive introduction to algorithmic fairness, covering key concepts, sources of bias, and practical mitigation strategies. Through expert-led lectures and hands-on demonstrations, participants will explore real-world case studies, fairness evaluation techniques, and tools for bias assessment. By the end, attendees will be equipped to integrate fairness principles into their machine learning workflows, fostering more equitable AI in healthcare.
Schedule
TDC
Organizers
Aasa Feragen, DTU Compute, Technical University of Denmark
Andrew King, King’s College London
Ben Glocker, Imperial College London
Enzo Ferrante, CONICET, Universidad Nacional del Litoral
Eike Petersen, DTU Compute, Technical University of Denmark
Esther Puyol-Antón, HeartFlow and King’s College London
Melanie Ganz-Benjaminsen, University of Copenhagen & Neurobiology Research Unit, Rigshospitalet
Veronika Cheplygina, IT University Copenhagen
Contact
Please direct any inquiries related to the workshop or this website to faimi-organizers@googlegroups.com.