This is a preview of subscription content, log in via an institution to check access.
References
Nakaura T, Yoshida N, Kobayashi N, Shiraishi K, Nagayama Y, Uetani H, Kidoh M, Hokamura M, Funama Y, Hirai T. Preliminary assessment of automated radiology report generation with generative pre-trained transformers: comparing results to radiologist-generated reports. Jpn J Radiol. 2024;42(2):190–200.
Beşler MS. The performance of the multimodal large language model GPT-4 on the European board of radiology examination sample test. Jpn J Radiol. 2024. https://doi.org/10.1007/s11604-024-01565-9.
Lecler A, Duron L, Soyer P. Revolutionizing radiology with GPT-based models: current applications, future possibilities and limitations of ChatGPT. Diagn Interv Imaging. 2023;104(6):269–74.
Jeblick K, Schachtner B, Dexl J, Mittermeier A, Stüber AT, Topalis J, Weber T, Wesp P, Sabel BO, Ricke J, Ingrisch M. ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports. Eur Radiol. 2023;5:1–9.
Bhayana R, Krishna S, Bleakney RR. Performance of ChatGPT on a radiology board-style examination: insights into current strengths and limitations. Radiology. 2023;307(5):e230582.
Acknowledgement
The author thanks Claude3 for discussions about the radiology and initial drafting.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Ray, P.P. Integrating AI in radiology: insights from GPT-generated reports and multimodal LLM performance on European Board of Radiology examinations. Jpn J Radiol (2024). https://doi.org/10.1007/s11604-024-01576-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11604-024-01576-6