在工作中学习:利用人工智能支持快速审查方法

IF 2.9 4区 医学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
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)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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
Journal of the Medical Library Association
Journal of the Medical Library Association INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
4.10
自引率
10.00%
发文量
39
审稿时长
26 weeks
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.
×
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