知识按钮:用于CDSS和临床研究的证据适应工具

Muhammad Afzal, Maqbool Hussain, W. A. Khan, Taqdir Ali, Sungyoung Lee, B. Kang
{"title":"知识按钮:用于CDSS和临床研究的证据适应工具","authors":"Muhammad Afzal, Maqbool Hussain, W. A. Khan, Taqdir Ali, Sungyoung Lee, B. Kang","doi":"10.1109/INISTA.2014.6873630","DOIUrl":null,"url":null,"abstract":"Healthcare domain is continuously growing with new knowledge emerged at different levels of clinical interest. At the same time, there is an increasing interest in the use of clinical decision support systems (CDSSs) to increase the healthcare quality and efficiency. Majorly the existing CDSSs are not designed to adapt scientific research in a well-established and automatic manner. Clinicians and researchers access the online resources on frequent basis for unmet questions during the course of patient care. They usually follow a dis-integrated approach to search for their required information from resources of their interest. Additionally, there is lack of defined mechanism to integrate the relevant knowledge for future use. To overcome the disintegrated and non-automatic approach, we introduce the concept of KnowledgeButton; a comprehensive model for evidence adaption from online credible knowledge sources in a well-defined and established manner. It saves the time of clinicians spend unnecessary in searching research evidence using disintegrated and manual mechanism. In this paper, we provide architecture design, workflows, and scenarios complemented with primary results. It covers walk-through from search query generation to evaluation of search results.","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"KnowledgeButton: An evidence adaptive tool for CDSS and clinical research\",\"authors\":\"Muhammad Afzal, Maqbool Hussain, W. A. Khan, Taqdir Ali, Sungyoung Lee, B. Kang\",\"doi\":\"10.1109/INISTA.2014.6873630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Healthcare domain is continuously growing with new knowledge emerged at different levels of clinical interest. At the same time, there is an increasing interest in the use of clinical decision support systems (CDSSs) to increase the healthcare quality and efficiency. Majorly the existing CDSSs are not designed to adapt scientific research in a well-established and automatic manner. Clinicians and researchers access the online resources on frequent basis for unmet questions during the course of patient care. They usually follow a dis-integrated approach to search for their required information from resources of their interest. Additionally, there is lack of defined mechanism to integrate the relevant knowledge for future use. To overcome the disintegrated and non-automatic approach, we introduce the concept of KnowledgeButton; a comprehensive model for evidence adaption from online credible knowledge sources in a well-defined and established manner. It saves the time of clinicians spend unnecessary in searching research evidence using disintegrated and manual mechanism. In this paper, we provide architecture design, workflows, and scenarios complemented with primary results. It covers walk-through from search query generation to evaluation of search results.\",\"PeriodicalId\":339652,\"journal\":{\"name\":\"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INISTA.2014.6873630\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INISTA.2014.6873630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

医疗保健领域是不断增长的新知识出现在不同层次的临床兴趣。与此同时,人们对临床决策支持系统(cdss)的使用越来越感兴趣,以提高医疗质量和效率。现有cdss的设计主要不是为了以一种完善和自动的方式适应科学研究。临床医生和研究人员经常访问在线资源,以解决患者护理过程中未解决的问题。他们通常遵循一种分解的方法,从他们感兴趣的资源中搜索他们所需的信息。此外,缺乏明确的机制来整合相关知识以供将来使用。为了克服分解和非自动的方法,我们引入了知识按钮的概念;一个全面的模型,以明确定义和建立的方式从在线可靠的知识来源中适应证据。它节省了临床医生使用崩解式和手动机制查找研究证据所花费的不必要时间。在本文中,我们提供了体系结构设计、工作流和与主要结果相补充的场景。它涵盖了从搜索查询生成到搜索结果评估的演练。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
KnowledgeButton: An evidence adaptive tool for CDSS and clinical research
Healthcare domain is continuously growing with new knowledge emerged at different levels of clinical interest. At the same time, there is an increasing interest in the use of clinical decision support systems (CDSSs) to increase the healthcare quality and efficiency. Majorly the existing CDSSs are not designed to adapt scientific research in a well-established and automatic manner. Clinicians and researchers access the online resources on frequent basis for unmet questions during the course of patient care. They usually follow a dis-integrated approach to search for their required information from resources of their interest. Additionally, there is lack of defined mechanism to integrate the relevant knowledge for future use. To overcome the disintegrated and non-automatic approach, we introduce the concept of KnowledgeButton; a comprehensive model for evidence adaption from online credible knowledge sources in a well-defined and established manner. It saves the time of clinicians spend unnecessary in searching research evidence using disintegrated and manual mechanism. In this paper, we provide architecture design, workflows, and scenarios complemented with primary results. It covers walk-through from search query generation to evaluation of search results.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信