Generative pre-trained transformer 4o (GPT-4o) in solving text-based multiple response questions for European Diploma in Radiology (EDiR): a comparative study with radiologists

Abstract

OBJECTIVES: This study aims to assess the accuracy of generative pre-trained transformer 4o (GPT-4o) in answering multiple response questions from the European Diploma in Radiology (EDiR) examination, comparing its performance to that of human candidates. MATERIALS AND METHODS: Results from 42 EDiR candidates across Europe were compared to those from 26 fourth-year medical students who answered exclusively using the ChatGPT-4o in a prospective study (October 2024). The challenge consisted of 52 recall or understanding-based EDiR multiple-response questions, all without visual inputs. RESULTS: The GPT-4o achieved a mean score of 82.1 ± 3.0%, significantly outperforming the EDiR candidates with 49.4 ± 10.5% (p < 0.0001). In particular, chatGPT-4o demonstrated higher true positive rates while maintaining lower false positive rates compared to EDiR candidates, with a higher accuracy rate in all radiology subspecialties (p < 0.0001) except informatics (p = 0.20). There was near-perfect agreement between GPT-4 responses (κ = 0.872) and moderate agreement among EDiR participants (κ = 0.334). Exit surveys revealed that all participants used the copy-and-paste feature, and 73% submitted additional questions to clarify responses. CONCLUSIONS: GPT-4o significantly outperformed human candidates in low-order, text-based EDiR multiple-response questions, demonstrating higher accuracy and reliability. These results highlight GPT-4o's potential in answering text-based radiology questions. Further research is necessary to investigate its performance across different question formats and candidate populations to ensure broader applicability and reliability. CRITICAL RELEVANCE STATEMENT: GPT-4o significantly outperforms human candidates in factual radiology text-based questions in the EDiR, excelling especially in identifying correct responses, with a higher accuracy rate compared to radiologists. KEY POINTS: In EDiR text-based questions, ChatGPT-4o scored higher (82%) than EDiR participants (49%). Compared to radiologists, GPT-4o excelled in identifying correct responses. GPT-4o responses demonstrated higher agreement (κ = 0.87) compared to EDiR candidates (κ = 0.33).

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