Kristin Rogers, Leah Hagerman, S. Neil-Sztramko, Maureen Dobbins
{"title":"在工作中学习:利用人工智能支持快速审查方法","authors":"Kristin Rogers, Leah Hagerman, S. Neil-Sztramko, Maureen Dobbins","doi":"10.5195/jmla.2024.1868","DOIUrl":null,"url":null,"abstract":"The National Collaborating Centre for Methods and Tools’ (NCCMT) Rapid Evidence Service conducts rapid reviews on priority questions to respond to the needs of public health decision-makers. Given the vast quantity of literature available, a key challenge of conducting rapid evidence syntheses is the time and effort required to manually screen large search results sets to identify and include all studies relevant to the research question within an accelerated timeline. To overcome this challenge, the NCCMT investigated the integration of artificial intelligence (AI) technologies into the title and abstract screening stage of the rapid review process to expedite the identification of studies relevant to the research question. \nThe NCCMT is funded by the Public Health Agenda of Canada and affiliated with McMaster University.","PeriodicalId":47690,"journal":{"name":"Journal of the Medical Library Association","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Learning on the job: using Artificial Intelligence to support rapid review methods\",\"authors\":\"Kristin Rogers, Leah Hagerman, S. Neil-Sztramko, Maureen Dobbins\",\"doi\":\"10.5195/jmla.2024.1868\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The National Collaborating Centre for Methods and Tools’ (NCCMT) Rapid Evidence Service conducts rapid reviews on priority questions to respond to the needs of public health decision-makers. Given the vast quantity of literature available, a key challenge of conducting rapid evidence syntheses is the time and effort required to manually screen large search results sets to identify and include all studies relevant to the research question within an accelerated timeline. To overcome this challenge, the NCCMT investigated the integration of artificial intelligence (AI) technologies into the title and abstract screening stage of the rapid review process to expedite the identification of studies relevant to the research question. \\nThe NCCMT is funded by the Public Health Agenda of Canada and affiliated with McMaster University.\",\"PeriodicalId\":47690,\"journal\":{\"name\":\"Journal of the Medical Library Association\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Medical Library Association\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.5195/jmla.2024.1868\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Medical Library Association","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.5195/jmla.2024.1868","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
摘要
国家方法与工具协作中心(NCCMT)的快速证据服务对优先问题进行快速审查,以满足公共卫生决策者的需求。鉴于现有文献数量庞大,进行快速证据综合的一个主要挑战是需要花费大量时间和精力来人工筛选大量搜索结果集,以便在较短的时间内确定并纳入与研究问题相关的所有研究。为了克服这一挑战,NCCMT 研究了将人工智能 (AI) 技术整合到快速审查流程的标题和摘要筛选阶段,以加快识别与研究问题相关的研究。NCCMT 由加拿大公共卫生议程(Public Health Agenda of Canada)资助,隶属于麦克马斯特大学(McMaster University)。
Learning on the job: using Artificial Intelligence to support rapid review methods
The National Collaborating Centre for Methods and Tools’ (NCCMT) Rapid Evidence Service conducts rapid reviews on priority questions to respond to the needs of public health decision-makers. Given the vast quantity of literature available, a key challenge of conducting rapid evidence syntheses is the time and effort required to manually screen large search results sets to identify and include all studies relevant to the research question within an accelerated timeline. To overcome this challenge, the NCCMT investigated the integration of artificial intelligence (AI) technologies into the title and abstract screening stage of the rapid review process to expedite the identification of studies relevant to the research question.
The NCCMT is funded by the Public Health Agenda of Canada and affiliated with McMaster University.
期刊介绍:
The Journal of the Medical Library Association (JMLA) is an international, peer-reviewed journal published quarterly that aims to advance the practice and research knowledgebase of health sciences librarianship. The most current impact factor for the JMLA (from the 2007 edition of Journal Citation Reports) is 1.392.