Response to Letter to the Editor from Partha Pratim Ray: ‘Integrating AI in radiology: insights from GPT-generated reports and multimodal LLM performance on European Board of Radiology examinations’
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11604-024-01626-z.pdf
Reference5 articles.
1. Ray PP. Integrating AI in radiology: insights from GPT-generated reports and multimodal LLM performance on European board of radiology examinations. Jpn J Radiol. 2024. (Epub ahead of print).
2. Nakaura T, Yoshida N, Kobayashi N, Shiraishi K, Nagayama Y, Uetani H, et al. Preliminary assessment of automated radiology report generation with generative pre-trained transformers: comparing results to radiologist-generated reports. Jpn J Radiol. 2024;42:190–200.
3. 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. (Epub ahead of print).
4. Hirano Y, Hanaoka S, Nakao T, Miki S, Kikuchi T, Nakamura Y et al. GPT-4 turbo with vision fails to outperform text-only GPT-4 Turbo in the Japan Diagnostic Radiology Board Examination. Jpn J Radiol. 2024. (Epub ahead of print).
5. Toyama Y, Harigai A, Abe M, Nagano M, Kawabata M, Seki Y, et al. Performance evaluation of ChatGPT, GPT-4, and Bard on the official board examination of the Japan Radiology Society. Jpn J Radiol. 2024;42:201–7.
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