人工智能多语种口译和放射学临床语言评估(AI-MIRACLE)。

IF 3 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Journal of Personalized Medicine Pub Date : 2024-08-30 DOI:10.3390/jpm14090923
Praneet Khanna, Gagandeep Dhillon, Venkata Buddhavarapu, Ram Verma, Rahul Kashyap, Harpreet Grewal
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引用次数: 0

摘要

AI-MIRACLE 研究调查了使用大型语言模型 (LLM) ChatGPT 4.0 将放射学报告翻译成多国语言并加以简化的效果,旨在提高患者的理解能力。研究评估了该模型在美国使用最多的语言中的表现,强调了为非医学读者翻译和简化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并简化为越南语、他加禄语、西班牙语、普通话和阿拉伯语。印地语被用作验证问卷的初步测试语言。通过向双语医生分发谷歌表格调查来评估其性能,以评估 ChatGPT 4 提供的简化文本的翻译准确性和清晰度。来自 24 位参与者的回答显示了不同的结果。这项研究强调了该模型在不同语言中取得的不同成功,同时也强调了其潜在应用和局限性。ChatGPT 4.0 有望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能力。但是,不同语言的表现并不一致,这表明需要进一步完善人工智能模型,并对其进行更全面的培训,以处理不同的医疗环境和语言。这项研究强调了 LLM 在改善医疗沟通和患者理解能力方面的作用,同时也表明需要继续推进人工智能技术的发展,尤其是在低资源语言的翻译方面。
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Artificial Intelligence in Multilingual Interpretation and Radiology Assessment for Clinical Language Evaluation (AI-MIRACLE).

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.

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来源期刊
Journal of Personalized Medicine
Journal of Personalized Medicine Medicine-Medicine (miscellaneous)
CiteScore
4.10
自引率
0.00%
发文量
1878
审稿时长
11 weeks
期刊介绍: Journal of Personalized Medicine (JPM; ISSN 2075-4426) is an international, open access journal aimed at bringing all aspects of personalized medicine to one platform. JPM publishes cutting edge, innovative preclinical and translational scientific research and technologies related to personalized medicine (e.g., pharmacogenomics/proteomics, systems biology). JPM recognizes that personalized medicine—the assessment of genetic, environmental and host factors that cause variability of individuals—is a challenging, transdisciplinary topic that requires discussions from a range of experts. For a comprehensive perspective of personalized medicine, JPM aims to integrate expertise from the molecular and translational sciences, therapeutics and diagnostics, as well as discussions of regulatory, social, ethical and policy aspects. We provide a forum to bring together academic and clinical researchers, biotechnology, diagnostic and pharmaceutical companies, health professionals, regulatory and ethical experts, and government and regulatory authorities.
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