{"title":"Evidence Hub: A place to exchange medical knowledge and form communities","authors":"Kenny Hong, Druvinka Bandaranayake, Guy Tsafnat","doi":"10.1002/lrh2.10387","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Introduction</h3>\n \n <p>Medical knowledge is complex and constantly evolving, making it challenging to disseminate and retrieve effectively. To address these challenges, researchers are exploring the use of formal knowledge representations that can be easily interpreted by computers.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Evidence Hub is a new, free, online platform that hosts computable clinical knowledge in the form of “Knowledge Objects”. These objects represent various types of computer-interpretable knowledge. The platform includes features that encourage advancing medical knowledge, such as public discussion threads for civil discourse about each Knowledge Object, thus building communities of interest that can form and reach consensus on the correctness, applicability, and proper use of the object. Knowledge Objects are maintained by volunteers and published on Evidence Hub under GPL 2.0. Peer review and quality assurance are provided by volunteers.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Users can explore Evidence Hub and participate in discussions using a web browser. An application programming interface allows applications to register themselves as handlers of specific object types and provide editing and execution capabilities for particular object types.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>By providing a platform for computable clinical knowledge and fostering discussion and collaboration, Evidence Hub improves the dissemination and use of medical knowledge.</p>\n </section>\n </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"7 4","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.10387","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning Health Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/lrh2.10387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 1
Abstract
Introduction
Medical knowledge is complex and constantly evolving, making it challenging to disseminate and retrieve effectively. To address these challenges, researchers are exploring the use of formal knowledge representations that can be easily interpreted by computers.
Methods
Evidence Hub is a new, free, online platform that hosts computable clinical knowledge in the form of “Knowledge Objects”. These objects represent various types of computer-interpretable knowledge. The platform includes features that encourage advancing medical knowledge, such as public discussion threads for civil discourse about each Knowledge Object, thus building communities of interest that can form and reach consensus on the correctness, applicability, and proper use of the object. Knowledge Objects are maintained by volunteers and published on Evidence Hub under GPL 2.0. Peer review and quality assurance are provided by volunteers.
Results
Users can explore Evidence Hub and participate in discussions using a web browser. An application programming interface allows applications to register themselves as handlers of specific object types and provide editing and execution capabilities for particular object types.
Conclusions
By providing a platform for computable clinical knowledge and fostering discussion and collaboration, Evidence Hub improves the dissemination and use of medical knowledge.