改善从临床文本中提取信息的研究报告质量:制定基于共识的报告准则的议定书
Daniel Reichenpfader1,2, Henning Müller3,4, Kerstin Denecke1
1Institute for Patient-Centered Digital Health, Department of Engineering and Computer Science, Bern University of Applied Sciences, Quellgasse 21, Biel, 2502, Switzerland, 41 31 848 60 93.
JMIR research protocols
|September 24, 2025
概括
制定临床信息提取 (CINEX) 准则有助于改善临床信息提取研究的报告. 这份经过专家验证的指南确保了医疗保健人工智能研究的透明度和可重复性.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床自然语言处理 临床自然语言处理
背景情况:
- 临床信息提取 (IE) 研究中不一致的报告实践阻碍了医疗保健的进步.
- 现有的指导方针不足以解决IE研究的独特挑战,导致报告异质性.
- 医疗保健框架中的当前人工智能经常忽视基于文本的IE,而是专注于预测建模或临床试验.
研究的目的:
- 制定临床信息提取 (CINEX) 指南,为临床IE研究制定基于共识的报告标准.
- 为满足临床IE研究的具体需求,提高研究报告的质量和一致性.
主要方法:
- 进行了一项涉及领域专家的3轮电子Delphi (eDelphi) 研究.
- 在MEDINFO 2025的混合共识会议上,最终确定了报告项目.
- 准则的制定遵循了既定方法,并预先定义了共识值.
主要成果:
- 起草了一套初步的28个报告项目,跨越5个维度 (信息模型,架构,数据,注释,结果).
- 在eDelphi过程中,这些项目得到了改进,以达到专家的共识.
- 该指南旨在技术不可知,涵盖各种IE方法.
结论:
- CINEX指南为报告临床IE研究提供了结构化,经专家验证的指导.
- 实施CINEX将提高医疗保健IE研究的透明度,可复制性和可比性.
- 传播将包括一个解释性文件,以支持广泛采用.
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