Exploring the accuracy of embedded ChatGPT-4 and ChatGPT-4o in generating BI-RADS scores: a pilot study in radiologic
Dan Nguyen1, Arya Rao2, Aneesh Mazumder3
1University of Massachusetts Chan Medical School, Worcester, MA, United States.
Abstract:
This study evaluates the accuracy of ChatGPT-4 and ChatGPT-4o in generating Breast Imaging Reporting and Data System (BI-RADS) scores from radiographic images. We tested both models using 77 breast cancer images from radiopaedia.org, including mammograms and ultrasounds. Images were analyzed in separate sessions to avoid bias. ChatGPT-4 and ChatGPT-4o achieved a 66.2 % accuracy across all BI-RADS cases. Performance was highest in BI-RADS 5 cases, with ChatGPT-4 and ChatGPT4o scoring 84.4 % and 88.9 %, respectively. However, both models struggled with BIRADS 1-3 cases, often assigning higher severity ratings. This study highlights the limitations of current LLMs in accurately grading these images and emphasizes the need for further research in these technologies before clinical integration.
