评估人工智能根据血管外科科学论文摘要生成的非专业人士摘要

Walter Dorigo MD , Elena Giacomelli MD, PhD , Cristiano Calvagna MD , Filippo Griselli MD , Sara Speziali MD , Aaron Thomas Fargion MD , Sandro Lepidi MD , Raffaele Pulli MD , Mario D'Oria MD
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摘要

背景本研究旨在评估人工智能(AI)语言模型 ChatGPT 3.5 在根据血管外科研究摘要生成可读且准确的非专业人士摘要方面的功效。根据既定方法设计了用于编写非专业人士摘要的 ChatGPT 提示。对原始摘要和 ChatGPT 生成的摘要进行了可读性测量和等级评估比较。两名血管外科医生对 ChatGPT 摘要的清晰度和正确性进行了随机抽样评估。使用 t 检验比较了原始摘要与 ChatGPT 生成的非专业摘要的可读性得分。此外,还根据摘要主题进行了子分析。结果 数据库共收录了 150 篇论文。原始摘要和人工智能生成的摘要在可读性测量和等级评估方面存在明显的统计学差异,表明后者的可读性更高(原始摘要的平均全局可读性分数为 36.6 ± 13.8,人工智能生成的摘要为 50.5 ± 11.1;P < .001)。这一趋势在不同的摘要主题和期刊中都持续存在。虽然一位医生认为所有摘要都是正确的,但另一位医生指出有 32% 的摘要不准确,平均评分分别为 4.0 分和 4.7 分,且观察者之间没有一致性(k 值 = -0.1)。
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Evaluation of artificial intelligence-generated layperson's summaries from abstracts of vascular surgical scientific papers

Background

This study aimed to assess the efficacy of ChatGPT 3.5, an artificial intelligence (AI) language model, in generating readable and accurate layperson's summaries from abstracts of vascular surgery studies.

Methods

Abstracts from four leading vascular surgery journals published between October 2023 and December 2023 were used. A ChatGPT prompt for developing layperson's summaries was designed based on established methodology. Readability measures and grade-level assessments were compared between original abstracts and ChatGPT-generated summaries. Two vascular surgeons evaluated a randomized sample of ChatGPT summaries for clarity and correctness. Readability scores of original abstracts were compared with ChatGPT-generated layperson's summaries using a t test. Moreover, a subanalysis based on abstract topics was performed. Cohen's kappa assessed interrater reliability for accuracy and clarity.

Results

One-hundred fifty papers were included in the database. Statistically significant differences were observed in readability measures and grade-level assessments between original abstracts and AI-generated summaries, indicating improved readability in the latter (mean Global Readability Score of 36.6 ± 13.8 in the original abstract and of 50.5 ± 11.1 in the AI-generated summary; P < .001). This trend persisted across abstract topics and journals. Although one physician found all summaries correct, the other noted inaccuracies in 32% of cases, with mean rating scores of 4.0 and 4.7, respectively, and no interobserver agreement (k value = −0.1).

Conclusions

ChatGPT demonstrates usefulness in producing patient-friendly summaries from scientific abstracts in vascular surgery, although the accuracy and quality of AI-generated summaries warrant further scrutiny.

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