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Japanese Journal of Radiology

02-05-2024 | Diagnostic Radiology | Letter to the Editor

Response to Letter to the Editor from Muhammed Said Beşler et al.: “The Performance of the Multimodal Large Language Model GPT-4 on the European Board of Radiology Examination Sample Test”

Authors: Takeshi Nakaura, Toshinori Hirai

Published in: Japanese Journal of Radiology

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Excerpt

Thank you for sharing this insightful letter regarding the potential of multimodal large language models (LLMs) in diagnostic radiology [1]. The author’s perspective on GPT-4’s capability to assess clinical case scenarios provides valuable insights into the future of AI-assisted radiology. …
Literature
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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.CrossRefPubMed
3.
Ueda D, Kakinuma T, Fujita S, Kamagata K, Fushimi Y, Ito R, et al. Fairness of artificial intelligence in healthcare: review and recommendations. Jpn J Radiol. 2024;42:3–15.CrossRefPubMed
4.
Metadata
Title
Response to Letter to the Editor from Muhammed Said Beşler et al.: “The Performance of the Multimodal Large Language Model GPT-4 on the European Board of Radiology Examination Sample Test”
Authors
Takeshi Nakaura
Toshinori Hirai
Publication date
02-05-2024
Publisher
Springer Nature Singapore
Published in
Japanese Journal of Radiology
Print ISSN: 1867-1071
Electronic ISSN: 1867-108X
DOI
https://doi.org/10.1007/s11604-024-01577-5