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人工智能生成的科学文献:批判性评价。

Artificial Intelligence-Generated Scientific Literature: A Critical Appraisal.

机构信息

Section of Allergy, Asthma & Immunology, Department of Medicine, Pennsylvania State University College of Medicine, Hershey, Pa.

Division of Allergy & Immunology, Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, Pa.

出版信息

J Allergy Clin Immunol Pract. 2024 Jan;12(1):106-110. doi: 10.1016/j.jaip.2023.10.010. Epub 2023 Oct 12.

Abstract

BACKGROUND

Review articles play a critical role in informing medical decisions and identifying avenues for future research. With the introduction of artificial intelligence (AI), there has been a growing interest in the potential of this technology to transform the synthesis of medical literature. Open AI's Generative Pre-trained Transformer (GPT-4) (Open AI Inc, San Francisco, CA) tool provides access to advanced AI that is able to quickly produce medical literature following only simple prompts. The accuracy of the generated articles requires review, especially in subspecialty fields like Allergy/Immunology.

OBJECTIVE

To critically appraise AI-synthesized allergy-focused minireviews.

METHODS

We tasked the GPT-4 Chatbot with generating 2 1,000-word reviews on the topics of hereditary angioedema and eosinophilic esophagitis. Authors critically appraised these articles using the Joanna Briggs Institute (JBI) tool for text and opinion and additionally evaluated domains of interest such as language, reference quality, and accuracy of the content.

RESULTS

The language of the AI-generated minireviews was carefully articulated and logically focused on the topic of interest; however, reviewers of the AI-generated articles indicated that the AI-generated content lacked depth, did not appear to be the result of an analytical process, missed critical information, and contained inaccurate information. Despite being provided instruction to utilize scientific references, the AI chatbot relied mainly on freely available resources, and the AI chatbot fabricated references.

CONCLUSIONS

The AI holds the potential to change the landscape of synthesizing medical literature; however, apparent inaccurate and fabricated information calls for rigorous evaluation and validation of AI tools in generating medical literature, especially on subjects associated with limited resources.

摘要

背景

综述文章在为医疗决策提供信息和确定未来研究方向方面发挥着关键作用。随着人工智能(AI)的引入,人们对这项技术在改变医学文献综合方面的潜力产生了浓厚的兴趣。Open AI 的生成式预训练转换器(GPT-4)(Open AI Inc,旧金山,CA)工具提供了对高级 AI 的访问,它能够仅通过简单的提示快速生成医学文献。生成文章的准确性需要进行审查,特别是在过敏/免疫学等亚专科领域。

目的

批判性地评价 AI 合成的过敏重点迷你综述。

方法

我们要求 GPT-4 聊天机器人生成 2 篇 1000 字的综述,主题分别为遗传性血管性水肿和嗜酸性食管炎。作者使用 Joanna Briggs 研究所(JBI)的文本和观点工具对这些文章进行了批判性评价,并对语言、参考质量和内容准确性等感兴趣的领域进行了评价。

结果

AI 生成的迷你综述的语言表达准确,逻辑上紧扣感兴趣的主题;然而,AI 生成文章的评论者表示,AI 生成的内容缺乏深度,似乎不是分析过程的结果,遗漏了关键信息,并且包含不准确的信息。尽管 AI 被指示使用科学参考资料,但 AI 聊天机器人主要依赖于免费的可用资源,并且 AI 聊天机器人伪造了参考资料。

结论

AI 有可能改变合成医学文献的格局;然而,明显不准确和伪造的信息需要对 AI 工具在生成医学文献方面进行严格的评估和验证,特别是在与有限资源相关的主题上。

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