March 24, 2022
‘Off label’ use of imaging databases could lead to bias in AI algorithms, study finds
A paper with lead author EECS postdoc Efrat Shimron and co-authors EECS graduate student Ke Wang, UT Austin professor Jonathan Tamir (EECS PhD ’18), and EECS Prof. Michael Lustig shows that algorithms trained using “off-label” or misapplied massive, open-source datasets are subject to integrity-compromising biases. The study, which was published in…