Researchers from the University of Ulsan in Seoul, South Korea recently developed and tested a deep-learning algorithm that was successful in a study of over 3.3 million chest radiographs.
The team reported that the algorithm could successfully triage pairs of chest radiographs showing no change while detecting urgent interval changes during longitudinal follow-up.
Julianna Czum, MD, from Johns Hopkins University wrote an editorial accompanying the study. She spoke with AuntMinnie.com to discuss its implications, how such a method could help mitigate burnout for emergency radiologists, and how AI continues its movement into clinical workflows.
