Automated vetting of radiology referrals: exploring NLP and ML approaches
As computed tomography (CT) sees an increase in utilization, inappropriate imaging has been seen as a significant concern; however, manual justification audits of radiology referrals are extremely time-consuming and carry a heavy financial burden. Therefore, the authors of this study aimed to retrospectively audit the justification of brain CT referrals by using natural language processing (NLP) and traditional machine learning