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ChatGPT 在肿瘤放疗患者和医护人员中的优势和劣势

Current Strengths and Weaknesses of ChatGPT as a Resource for Radiation Oncology Patients and Providers.

机构信息

Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.

Department of Radiation Oncology, Duke University School of Medicine, Durham, North Carolina; Radiation Oncology Clinical Service, Durham VA Health Care System, Durham, North Carolina.

出版信息

Int J Radiat Oncol Biol Phys. 2024 Mar 15;118(4):905-915. doi: 10.1016/j.ijrobp.2023.10.020. Epub 2023 Oct 30.

Abstract

PURPOSE

Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence program that uses natural language processing to generate conversational-style responses to questions or inputs, is increasingly being used by both patients and health care professionals. This study aims to evaluate the accuracy and comprehensiveness of ChatGPT in radiation oncology-related domains, including answering common patient questions, summarizing landmark clinical research studies, and providing literature reviews with specific references supporting current standard-of-care clinical practice in radiation oncology.

METHODS AND MATERIALS

We assessed the performance of ChatGPT version 3.5 (ChatGPT3.5) in 3 areas. We evaluated ChatGPT3.5's ability to answer 28 templated patient-centered questions applied across 9 cancer types. We then tested ChatGPT3.5's ability to summarize specific portions of 10 landmark studies in radiation oncology. Next, we used ChatGPT3.5 to identify scientific studies supporting current standard-of-care practice in clinical radiation oncology for 5 different cancer types. Each response was graded independently by 2 reviewers, with discordant grades resolved by a third reviewer.

RESULTS

ChatGPT3.5 frequently generated inaccurate or incomplete responses. Only 39.7% of responses to patient-centered questions were considered correct and comprehensive. When summarizing landmark studies in radiation oncology, 35.0% of ChatGPT3.5's responses were accurate and comprehensive, improving to 43.3% when provided the full text of the study. ChatGPT3.5's ability to present a list of studies related to standard-of-care clinical practices was also unsatisfactory, with 50.6% of the provided studies fabricated.

CONCLUSIONS

ChatGPT should not be considered a reliable radiation oncology resource for patients or providers at this time, as it frequently generates inaccurate or incomplete responses. However, natural language programming-based artificial intelligence programs are rapidly evolving, and future versions of ChatGPT or similar programs may demonstrate improved performance in this domain.

摘要

目的

聊天生成预训练转换器(ChatGPT)是一种人工智能程序,它使用自然语言处理生成对话式响应来回答问题或输入,越来越多地被患者和医疗保健专业人员使用。本研究旨在评估 ChatGPT 在放射肿瘤学相关领域的准确性和全面性,包括回答常见的患者问题、总结具有里程碑意义的临床研究、以及提供具有特定参考文献的文献综述,以支持当前放射肿瘤学的标准临床实践。

方法和材料

我们评估了 ChatGPT 版本 3.5(ChatGPT3.5)在 3 个方面的性能。我们评估了 ChatGPT3.5 回答 28 个模板化以患者为中心的问题的能力,这些问题适用于 9 种癌症类型。然后,我们测试了 ChatGPT3.5 总结 10 项具有里程碑意义的放射肿瘤学研究特定部分的能力。接下来,我们使用 ChatGPT3.5 为 5 种不同癌症类型确定支持当前临床放射肿瘤学标准护理实践的科学研究。每个回复由 2 位审阅者独立评分,意见不一致的回复由第 3 位审阅者解决。

结果

ChatGPT3.5 经常生成不准确或不完整的回复。只有 39.7%的患者中心问题的回复被认为是正确和全面的。当总结放射肿瘤学中的里程碑研究时,ChatGPT3.5 的 35.0%的回复是准确和全面的,当提供研究的全文时,提高到 43.3%。ChatGPT3.5 提供与标准护理临床实践相关的研究列表的能力也不理想,提供的研究中有 50.6%是伪造的。

结论

目前,ChatGPT 不应被视为患者或提供者在放射肿瘤学方面的可靠资源,因为它经常生成不准确或不完整的回复。然而,基于自然语言编程的人工智能程序正在迅速发展,未来版本的 ChatGPT 或类似程序在这一领域可能会表现出更好的性能。

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