Suppr超能文献

临床试验中资格标准复杂性分析

Analysis of eligibility criteria complexity in clinical trials.

作者信息

Ross Jessica, Tu Samson, Carini Simona, Sim Ida

机构信息

Dept of Psychiatry, Veteran's Administration Medical Center, San Francisco, CA;

出版信息

Summit Transl Bioinform. 2010 Mar 1;2010:46-50.

Abstract

Formal, computer-interpretable representations of eligibility criteria would allow computers to better support key clinical research and care use cases such as eligibility determination. To inform the development of such formal representations for eligibility criteria, we conducted this study to characterize and quantify the complexity present in 1000 eligibility criteria randomly selected from studies in ClinicalTrials.gov. We classified the criteria by their complexity, semantic patterns, clinical content, and data sources. Our analyses revealed significant semantic and clinical content variability. We found that 93% of criteria were comprehensible, with 85% of these criteria having significant semantic complexity, including 40% relying on temporal data. We also identified several domains of clinical content. Using the findings of the study as requirements for computer-interpretable representations of eligibility, we discuss the challenges for creating such representations for use in clinical research and practice.

摘要

合格标准的形式化、计算机可解释表示将使计算机能够更好地支持关键的临床研究和医疗用例,如合格性判定。为了为合格标准的此类形式化表示的开发提供信息,我们开展了本研究,以描述和量化从ClinicalTrials.gov上的研究中随机选取的1000条合格标准中存在的复杂性。我们根据标准的复杂性、语义模式、临床内容和数据来源对其进行了分类。我们的分析揭示了显著的语义和临床内容变异性。我们发现93%的标准是可理解的,其中85%的标准具有显著的语义复杂性,包括40%依赖时间数据。我们还确定了几个临床内容领域。利用该研究的结果作为合格性计算机可解释表示的要求,我们讨论了创建此类表示以用于临床研究和实践所面临的挑战。

相似文献

4
EliXR: an approach to eligibility criteria extraction and representation.EliXR:一种资格标准提取和表示方法。
J Am Med Inform Assoc. 2011 Dec;18 Suppl 1(Suppl 1):i116-24. doi: 10.1136/amiajnl-2011-000321. Epub 2011 Jul 31.
5
Formal representation of eligibility criteria: a literature review.资格标准的形式化表示:文献综述。
J Biomed Inform. 2010 Jun;43(3):451-67. doi: 10.1016/j.jbi.2009.12.004. Epub 2009 Dec 23.

引用本文的文献

1
A bibliometric analysis of the advance of artificial intelligence in medicine.医学领域人工智能进展的文献计量分析
Front Med (Lausanne). 2025 Feb 21;12:1504428. doi: 10.3389/fmed.2025.1504428. eCollection 2025.
10
Uncovering key clinical trial features influencing recruitment.揭示影响招募的关键临床试验特征。
J Clin Transl Sci. 2023 Sep 4;7(1):e199. doi: 10.1017/cts.2023.623. eCollection 2023.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验