在泌尿瘤学临床试验中对非专业人士摘要的可读性优化:来自BRIDGE-AI 8研究的结果
Ilicia Cano1,2, Aalamnoor Pannu1,2, Ethan Layne1,2
1USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA.
Current oncology (Toronto, Ont.)
|December 24, 2025
概括
像Pub2Post这样的生成人工智能 (GAI) 工具显著提高了患者泌尿瘤学临床试验摘要的可读性和完整性. 这些人工智能生成的摘要达到中学阅读水平,增强患者的理解和参与研究.
科学领域:
- 尿道瘤学 尿道瘤学
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
背景情况:
- 可访问的健康信息对于患者参与临床研究至关重要.
- 目前的临床试验.gov简要介绍对于普通人来说往往太复杂了.
- 泌尿瘤学试验需要对患者友好的摘要,以提高参与度.
研究的目的:
- 评估一个生成人工智能 (GAI) 工具Pub2Post,用于创建可读和完整的非专业人士摘要的泌尿瘤学临床试验.
- 将GAI生成的摘要与临床试验.gov.gov上现有的公开摘要进行比较.
主要方法:
- 从ClinicalTrials.gov.gov选出了20个积极招募泌尿外科瘤学临床试验的研究人员.
- 用Pub2Post工具为每个试验创建了GAI生成的摘要.
- 摘要分析了八个领域的可读性 (Flesch阅读易度得分),年级水平,文本复杂性和内容包含.
主要成果:
- 由GAI生成的摘要显示可读性显著改善 (平均FRES 73.3比17.0,p < 0.0001),符合中学阅读水平标准.
- 人工智能总结实现了100%包含基本内容元素.
- 与原始摘要相比,GAI摘要具有更简单的语法和更少的词汇复杂性.
结论:
- GAI工具Pub2Post有效地为泌尿瘤学临床试验生成面向患者的摘要,这些摘要既可访问又全面.
- 通过提高摘要质量,GAI有可能提高患者对临床研究的理解和参与.
- 这项技术可以弥合复杂的医疗信息和患者理解之间的差距.
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