Radiologists share tips to prevent AI bias
OAK BROOK, Ill. – Radiologists, computer scientists and informaticists outline pitfalls and best practices to mitigate bias in artificial intelligence (AI) models in an article published today in Radiology, a journal of the Radiological Society of North America (RSNA).
“AI has the potential to revolutionize radiology by improving diagnostic accuracy and access to care,” said lead author Paul H. Yi, M.D., associate member (associate professor) in the Department of Radiology and director of Intelligent Imaging Informatics at ...