Tracking down patients’ prior studies is a time-consuming aspect of radiologist workflow, but new research suggests deep learning could help significantly reduce that burden. 

Published in Academic Radiology on May 18, the study details how experts were able to shave approximately 40% off radiologists’ interpretation times by using a deep learning tool to identify patients’ prior relevant imaging. Not only was the tool—TimeLens—effective at identifying exams, it also flagged findings of interest from prior exams for radiologists to review. 

The authors of the new paper suggested…