Fairness of AI in Medical Imaging

Dr. Celi is the principal investigator behind the Medical Information Mart for Intensive Care (MIMIC) and its offsprings, MIMIC-CXR, MIMIC-ED, MIMIC-ECHO, and MIMIC-ECG. With close to 100k users worldwide, an open codebase, and close to 10k publications in Google Scholar, the datasets have undoubtedly shaped the course of machine learning in healthcare in the United States and beyond. His group has written 3 open-access textbooks: “Secondary Analysis of Electronic Health Records” in 2016, “Global Health Informatics: Principles of eHealth and mHealth to Improve Quality of Care” in 2017, and “Leveraging Data Science for Global Health” in 2020. The first has been downloaded close to 2 million times and translated into Mandarin, Spanish, Korean and Portuguese. The group has created two open online courses, “Global Health Informatics'' and “Collaborative Data Science for Healthcare”. Finally, in partnership with hospitals, universities and professional societies across the globe, Dr. Celi and his team have organized over 100 health data science events in 40 countries in the last decade, bringing together students, clinicians, researchers, and engineers to leverage data routinely collected in the process of care.

Talk: Learning in the Age of AI

Fairness in medical imaging is but one part of a complex ecosystem. Addressing fairness in medical imaging without acknowledging the elephant in the room is window washing at best. The elephant in the room is the systemic issues that create all the biases in the data in the first place. Addressing fairness in medical imaging once the models are developed may simply be polishing one cog of a wheel that remains stuck in mud. The machine learning community must not ignore the forest for the trees. But where to begin? We begin by promoting critical thinking. Rather than attempting to teach critical thinking - which is impossible since it must be discovered - educators should create environments of psychological safety where learners from diverse backgrounds can challenge each other with curiosity rather than hubris, fostering the kind of collaborative discovery that true critical thinking requires.