From text to image: challenges in integrating vision into ChatGPT for medical image interpretation
- PMID: 38819060
- PMCID: PMC11317956
- DOI: 10.4103/NRR.NRR-D-24-00165
From text to image: challenges in integrating vision into ChatGPT for medical image interpretation
References
-
- Horiuchi D, Tatekawa H, Oura T, Shimono T, Walston SL, Takita H, Matsushita S, Mitsuyama Y, Miki Y, Ueda D. Comparison of the diagnostic accuracy among GPT-4 based ChatGPT, GPT–4V based ChatGPT, and radiologists in musculoskeletal radiology. medRxiv [preprint] 2023 doi: https://doi.org/10.1101/2023.12.07.23299707.
-
- Ji ZW, Lee N, Frieske R, Yu T, Su D, Xu Y, Ishii E, Bang YJ, Madotto A, Fung P. Survey of hallucination in natural language generation. ACM Comput Surv. 2023;55:1–38.
-
- Koga S. Exploring the pitfalls of large language models: Inconsistency and inaccuracy in answering pathology board examination-style questions. Pathol Int. 2023;73:618–620. - PubMed
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