• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

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.

DOI:10.1371/journal.pone.0238290
PMID:32946464
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7500653/
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/a170b586b0cd/pone.0238290.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/e956cd4827fc/pone.0238290.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/f41857ab8a38/pone.0238290.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/7c8fef452690/pone.0238290.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/dae0a852f6ad/pone.0238290.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/9fe7b377d276/pone.0238290.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/707582ff6791/pone.0238290.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/a170b586b0cd/pone.0238290.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/e956cd4827fc/pone.0238290.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/f41857ab8a38/pone.0238290.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/7c8fef452690/pone.0238290.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/dae0a852f6ad/pone.0238290.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/9fe7b377d276/pone.0238290.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/707582ff6791/pone.0238290.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d005/7500653/a170b586b0cd/pone.0238290.g007.jpg

相似文献

1
An interactive retrieval system for clinical trial studies with context-dependent protocol elements.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。
PLoS One. 2020 Sep 18;15(9):e0238290. doi: 10.1371/journal.pone.0238290. eCollection 2020.
2
Textpresso: an ontology-based information retrieval and extraction system for biological literature.Textpresso：一个基于本体的生物文献信息检索与提取系统。
PLoS Biol. 2004 Nov;2(11):e309. doi: 10.1371/journal.pbio.0020309. Epub 2004 Sep 21.
3
SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services.SSWAP：一种用于语义 Web 服务的简单语义 Web 架构和协议。
BMC Bioinformatics. 2009 Sep 23;10:309. doi: 10.1186/1471-2105-10-309.
4
LAILAPS-QSM: A RESTful API and JAVA library for semantic query suggestions.Lailaps-QSM：用于语义查询建议的 RESTful API 和 JAVA 库。
PLoS Comput Biol. 2018 Mar 12;14(3):e1006058. doi: 10.1371/journal.pcbi.1006058. eCollection 2018 Mar.
5
Open Biomedical Ontology-based Medline exploration.基于开放生物医学本体的医学文献检索
BMC Bioinformatics. 2009 May 6;10 Suppl 5(Suppl 5):S6. doi: 10.1186/1471-2105-10-S5-S6.
6
BioLingua: a programmable knowledge environment for biologists.BioLingua：面向生物学家的可编程知识环境。
Bioinformatics. 2005 Jan 15;21(2):199-207. doi: 10.1093/bioinformatics/bth465. Epub 2004 Aug 12.
7
Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.在流行地区，服用抗叶酸抗疟药物的人群中，叶酸补充剂与疟疾易感性和严重程度的关系。
Cochrane Database Syst Rev. 2022 Feb 1;2(2022):CD014217. doi: 10.1002/14651858.CD014217.
8
Developing a modern web interface for database-driven bioinformatics tools.为数据库驱动的生物信息学工具开发一个现代的网络界面。
IEEE Eng Med Biol Mag. 2007 Mar-Apr;26(2):96-8. doi: 10.1109/memb.2007.335598.
9
Information retrieval in digital libraries: bringing search to the net.数字图书馆中的信息检索：将搜索带入网络。
Science. 1997 Jan 17;275(5298):327-34. doi: 10.1126/science.275.5298.327.
10
The LAILAPS search engine: relevance ranking in life science databases.LAILAPS搜索引擎：生命科学数据库中的相关性排名
J Integr Bioinform. 2010 Jan 15;7(2):110. doi: 10.2390/biecoll-jib-2010-110.

本文引用的文献

1
CDEK: Clinical Drug Experience Knowledgebase.CDEK：临床药物经验知识库。
Database (Oxford). 2019 Jan 1;2019. doi: 10.1093/database/baz087.
2
Concept embedding to measure semantic relatedness for biomedical information ontologies.概念嵌入用于测量生物医学信息本体的语义相似度。
J Biomed Inform. 2019 Jun;94:103182. doi: 10.1016/j.jbi.2019.103182. Epub 2019 Apr 19.
3
Network-based prediction of drug combinations.基于网络的药物组合预测。
Nat Commun. 2019 Mar 13;10(1):1197. doi: 10.1038/s41467-019-09186-x.
4
Comparison of Sales Income and Research and Development Costs for FDA-Approved Cancer Drugs Sold by Originator Drug Companies.原研药公司销售的美国 FDA 批准的抗癌药物的销售收入和研发成本比较。
JAMA Netw Open. 2019 Jan 4;2(1):e186875. doi: 10.1001/jamanetworkopen.2018.6875.
5
Federated electronic health records research technology to support clinical trial protocol optimization: Evidence from EHR4CR and the InSite platform.支持临床试验方案优化的联合电子健康记录研究技术：来自EHR4CR和InSite平台的证据。
J Biomed Inform. 2019 Feb;90:103090. doi: 10.1016/j.jbi.2018.12.004. Epub 2019 Jan 2.
6
Systems Pharmacology: Defining the Interactions of Drug Combinations.系统药理学：定义药物组合的相互作用。
Annu Rev Pharmacol Toxicol. 2019 Jan 6;59:21-40. doi: 10.1146/annurev-pharmtox-010818-021511. Epub 2018 Sep 27.
7
New Governance Mechanisms to Optimize Protocol Design.优化方案设计的新治理机制
Ther Innov Regul Sci. 2013 Nov;47(6):651-655. doi: 10.1177/2168479013494386.
8
The Impact of Protocol Amendments on Clinical Trial Performance and Cost.方案修正案对临床试验绩效和成本的影响。
Ther Innov Regul Sci. 2016 Jul;50(4):436-441. doi: 10.1177/2168479016632271.
9
Utilization of a Clinical Trial Management System for the Whole Clinical Trial Process as an Integrated Database: System Development.将临床试验管理系统用作集成数据库应用于整个临床试验过程：系统开发
J Med Internet Res. 2018 Apr 24;20(4):e103. doi: 10.2196/jmir.9312.
10
Trial watch: Trends in clinical trial design complexity.试验观察：临床试验设计复杂性的趋势
Nat Rev Drug Discov. 2017 May;16(5):307. doi: 10.1038/nrd.2017.65. Epub 2017 Apr 18.