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具有上下文相关协议元素的临床试验研究的交互式检索系统。

An interactive retrieval system for clinical trial studies with context-dependent protocol elements.

机构信息

Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.

Bio-Synergy Research Center, KAIST, Daejeon, Republic of Korea.

出版信息

PLoS One. 2020 Sep 18;15(9):e0238290. doi: 10.1371/journal.pone.0238290. eCollection 2020.

Abstract

A well-defined protocol for a clinical trial guarantees a successful outcome report. When designing the protocol, most researchers refer to electronic databases and extract protocol elements using a keyword search. However, state-of-the-art database systems only offer text-based searches for user-entered keywords. In this study, we present a database system with a context-dependent and protocol-element-selection function for successfully designing a clinical trial protocol. To do this, we first introduce a database for a protocol retrieval system constructed from individual protocol data extracted from 184,634 clinical trials and 13,210 frame structures of clinical trial protocols. The database contains a variety of semantic information that allows the filtering of protocols during the search operation. Based on the database, we developed a web application called the clinical trial protocol database system (CLIPS; available at https://corus.kaist.edu/clips). This system enables an interactive search by utilizing protocol elements. To enable an interactive search for combinations of protocol elements, CLIPS provides optional next element selection according to the previous element in the form of a connected tree. The validation results show that our method achieves better performance than that of existing databases in predicting phenotypic features.

摘要

一个明确的临床试验方案能保证成功的研究报告。在设计方案时,大多数研究人员会参考电子数据库,并使用关键词搜索来提取方案要素。然而,最先进的数据库系统仅提供基于用户输入关键字的文本搜索。在这项研究中,我们提出了一种具有上下文相关和方案要素选择功能的数据库系统,以成功设计临床试验方案。为此,我们首先引入了一个从 184634 项临床试验和 13210 个临床试验方案框架结构中提取的个体化方案数据构建的方案检索系统数据库。该数据库包含各种语义信息,允许在搜索操作期间过滤方案。基于该数据库,我们开发了一个名为临床试验方案数据库系统(CLIPS)的网络应用程序(可在 https://corus.kaist.edu/clips 上获得)。该系统通过利用方案要素实现交互式搜索。为了实现方案要素组合的交互式搜索,CLIPS 提供了根据前一个要素的可选下一个要素选择,以连接树的形式呈现。验证结果表明,我们的方法在预测表型特征方面的性能优于现有数据库。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/e956cd4827fc/pone.0238290.g001.jpg

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