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Article

Artificial Intelligence in Multilingual Interpretation and Radiology Assessment for Clinical Language Evaluation (AI-MIRACLE)

1
The University of Missouri-Kansas City School of Medicine, Kansas City, MO 64108, USA
2
Department of Internal Medicine, University of Maryland Baltimore Washington Medical Center, Glen Burnie, MD 21061, USA
3
Banner Baywood Medical Center, Banner Health, Mesa, AZ 85206, USA
4
Department of Sleep Medicine, Parkview Health System, Fort Wayne, IN 46845, USA
5
Department of Research, WellSpan Health, York, PA 17403, USA
6
Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN 55905, USA
7
Department of Radiology, College of Medicine, Florida State University, Pensacola, FL 32514, USA
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2024, 14(9), 923; https://doi.org/10.3390/jpm14090923
Submission received: 25 July 2024 / Revised: 17 August 2024 / Accepted: 27 August 2024 / Published: 30 August 2024
(This article belongs to the Section Methodology, Drug and Device Discovery)

Abstract

The AI-MIRACLE Study investigates the efficacy of using ChatGPT 4.0, a large language model (LLM), for translating and simplifying radiology reports into multiple languages, aimed at enhancing patient comprehension. The study assesses the model’s performance across the most spoken languages in the U.S., emphasizing the accuracy and clarity of translated and simplified radiology reports for non-medical readers. This study employed ChatGPT 4.0 to translate and simplify selected radiology reports into Vietnamese, Tagalog, Spanish, Mandarin, and Arabic. Hindi was used as a preliminary test language for validation of the questionnaire. Performance was assessed via Google form surveys distributed to bilingual physicians, which assessed the translation accuracy and clarity of simplified texts provided by ChatGPT 4. Responses from 24 participants showed mixed results. The study underscores the model’s varying success across different languages, emphasizing both potential applications and limitations. ChatGPT 4.0 shows promise in breaking down language barriers in healthcare settings, enhancing patient comprehension of complex medical information. However, the performance is inconsistent across languages, indicating a need for further refinement and more inclusive training of AI models to handle diverse medical contexts and languages. The study highlights the role of LLMs in improving healthcare communication and patient comprehension, while indicating the need for continued advancements in AI technology, particularly in the translation of low-resource languages.
Keywords: artificial intelligence; radiology; translation; ChatGPT 4.0 artificial intelligence; radiology; translation; ChatGPT 4.0

Share and Cite

MDPI and ACS Style

Khanna, P.; Dhillon, G.; Buddhavarapu, V.; Verma, R.; Kashyap, R.; Grewal, H. Artificial Intelligence in Multilingual Interpretation and Radiology Assessment for Clinical Language Evaluation (AI-MIRACLE). J. Pers. Med. 2024, 14, 923. https://doi.org/10.3390/jpm14090923

AMA Style

Khanna P, Dhillon G, Buddhavarapu V, Verma R, Kashyap R, Grewal H. Artificial Intelligence in Multilingual Interpretation and Radiology Assessment for Clinical Language Evaluation (AI-MIRACLE). Journal of Personalized Medicine. 2024; 14(9):923. https://doi.org/10.3390/jpm14090923

Chicago/Turabian Style

Khanna, Praneet, Gagandeep Dhillon, Venkata Buddhavarapu, Ram Verma, Rahul Kashyap, and Harpreet Grewal. 2024. "Artificial Intelligence in Multilingual Interpretation and Radiology Assessment for Clinical Language Evaluation (AI-MIRACLE)" Journal of Personalized Medicine 14, no. 9: 923. https://doi.org/10.3390/jpm14090923

APA Style

Khanna, P., Dhillon, G., Buddhavarapu, V., Verma, R., Kashyap, R., & Grewal, H. (2024). Artificial Intelligence in Multilingual Interpretation and Radiology Assessment for Clinical Language Evaluation (AI-MIRACLE). Journal of Personalized Medicine, 14(9), 923. https://doi.org/10.3390/jpm14090923

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