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. 2024 Jul 12;35(1):506–516. doi: 10.1007/s00330-024-10902-5

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 4 — A challenging case example for GPT-4-based ChatGPT. a Input texts (patient’s medical history and imaging findings) to ChatGPT. b Output texts generated by ChatGPT. The differential diagnoses are outlined in blue and the final diagnosis is outlined in red. While the differential diagnoses generated by ChatGPT include the correct diagnosis, the final diagnosis is incorrect in this case (true diagnosis: parosteal osteosarcoma) [35, 36]