FAIMI-MICCAI 2023 : Fairness of AI in Medical Imaging @ MICCAI 2023
Call For Papers
We invite the submission of papers for
FAIMI: The MICCAI 2023 Workshop on Fairness of AI in Medical Imaging.
Over the past several years, research on fairness, equity, and accountability in the context of machine learning has extensively demonstrated ethical risks in the deployment of machine learning systems in critical infrastructure, such as medical imaging. The FAIMI workshop aims to encourage and emphasize research on and discussion of fairness of AI within the medical imaging domain. We therefore invite the submission of papers, which will be selected for oral or poster presentation at the workshop. Topics include but are not limited to:
* Case studies providing evidence of and/or addressing bias in medical imaging
* Algorithmic fairness in medical imaging
* Methods for measuring/evaluating bias in medical imaging
* Methods for mitigating bias in medical imaging
* Ethical aspects of bias and fairness in medical imaging
* Legal aspects of bias and fairness in medical imaging
* Policy in the context of bias and fairness in medical imaging
The workshop proceedings will be published in the MICCAI workshops volumes of the Springer Lecture Notes Computer Science (LNCS) series. Selected papers will also be invited to present at the virtual FAIMI workshop tentatively scheduled for November 6th. Papers should be anonymized and at most 8 pages plus at most 2 extra pages of references using the LNCS format.
Submissions are made in CMT.
July 21st, 2023: Paper submission
August 11th, 2023: Notification of paper decisions
August 25th, 2023: Camera-ready deadline
October 8th, 2023: Workshop
Aasa Feragen, DTU Compute, Technical University of Denmark
Andrew King, King’s College London
Ben Glocker, Imperial College London
Daniel Moyer, Vanderbilt University
Enzo Ferrante, CONICET, Universidad Nacional del Litoral
Eike Petersen, DTU Compute, Technical University of Denmark
Esther Puyol, HeartFlow and King’s College London
Melanie Ganz-Benjaminsen, University of Copenhagen & Neurobiology Research Unit, Rigshospitalet
Veronika Cheplygina, IT University of Copenhagen
Please direct any inquiries related to the workshop or this website to email@example.com.