Khanna Praneet, Dhillon Gagandeep, Buddhavarapu Venkata, Verma Ram, Kashyap Rahul, Grewal Harpreet
The University of Missouri-Kansas City School of Medicine, Kansas City, MO 64108, USA.
Department of Internal Medicine, University of Maryland Baltimore Washington Medical Center, Glen Burnie, MD 21061, USA.
J Pers Med. 2024 Aug 30;14(9):923. doi: 10.3390/jpm14090923.
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.
AI-MIRACLE研究调查了使用大型语言模型ChatGPT 4.0将放射学报告翻译成多种语言并进行简化以提高患者理解能力的效果。该研究评估了该模型在美国使用最广泛的几种语言中的表现,重点关注为非医学读者提供的翻译和简化后的放射学报告的准确性和清晰度。本研究使用ChatGPT 4.0将选定的放射学报告翻译成越南语、他加禄语、西班牙语、普通话和阿拉伯语。印地语被用作问卷验证的初步测试语言。通过分发给双语医生的谷歌表单调查来评估性能,该调查评估了ChatGPT 4提供的简化文本的翻译准确性和清晰度。24名参与者的反馈结果喜忧参半。该研究强调了该模型在不同语言上取得的不同程度的成功,既突出了其潜在应用,也指出了局限性。ChatGPT 4.0在打破医疗环境中的语言障碍、提高患者对复杂医疗信息的理解方面显示出了前景。然而,其在不同语言上的表现并不一致,这表明需要进一步优化和对人工智能模型进行更具包容性的训练,以处理不同的医疗背景和语言。该研究突出了大型语言模型在改善医疗沟通和患者理解方面的作用,同时表明人工智能技术需要持续进步,特别是在低资源语言的翻译方面。