Email Alert RSS
Turn off MathJax
Article Contents
Article Navigation >  Medical Journal of Peking Union Medical College Hospital  > 0  > 
GUO Yujie, ZHANG Xueqin, SUN Wenyu, DENG Hongyong. Application of Automated Literature Screening Tools in Systematic Reviews[J]. Medical Journal of Peking Union Medical College Hospital. doi: 10.12290/xhyxzz.2023-0257
Citation: GUO Yujie, ZHANG Xueqin, SUN Wenyu, DENG Hongyong. Application of Automated Literature Screening Tools in Systematic Reviews[J]. Medical Journal of Peking Union Medical College Hospital. doi: 10.12290/xhyxzz.2023-0257
shu

Application of Automated Literature Screening Tools in Systematic Reviews

doi: 10.12290/xhyxzz.2023-0257

  • Science and Information Center, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

Funds:

National Natural Science Foundation of China (81873183)

  • Received Date: 2023-05-30
    Available Online: 2023-12-18
    Abstract
  • Systematic reviews are the basis of evidence-based medical research, and high-quality systematic reviews represent the highest level of evidence for evaluating treatment effects. Traditional systematic reviews are mainly done manually, especially the reading and screening of massive literature requires a lot of energy and time for clinicians, and the efficiency is low, which cannot meet the needs of rapid decision-making. This article systematically sorts out existing automated tools for systematic review literature screening, and analyzes their respective performance, characteristics, and usage to understand the current development status of this field and provide reference for related research and applications.
    • FullText(HTML)
  • loading
    • References(25)
  • [1] 杨丰春,徐晓巍,李姣.循证医学研究中的证据自动更新方法研究[J].中国数字医学,2022,17(1):44-49.
    [2] 徐昆明,钱堃,何艳屏等.中国近20年小儿烧伤流行病学的系统性评价[J].按摩与康复医学,2021,12(10):84-88.
    [3] 毛渤淳,陈圣恺,谢雨,姚攀,李春洁.经典深度学习算法对中文随机对照试验智能判别应用[J].中国循证医学杂志,2019,19(11):1262-1267.
    [4] Borah R, Brown A W, Capers P L, et al. Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry[J]. BMJ open, 2017, 7(2):e012545.
    [5] 张雪芹,张薇,郑培永,邓宏勇.计算机辅助系统评价方法学研究和应用[J].中国循证医学杂志,2021,21(1):111-116.
    [6] McKibbon K A, Wilczynski N L, Haynes R B, et al. Retrieving randomized controlled trials from medline:a comparison of 38 published search filters[J]. Health Information & Libraries Journal, 2009, 26(3):187-202.
    [7] Wallace B C, Noel-Storr A, Marshall I J, et al. Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach[J]. Journal of the American Medical Informatics Association, 2017, 24(6):1165-1168.
    [8] Marshall I J, Noel-Storr A, Kuiper J, et al. Machine learning for identifying randomized controlled trials:an evaluation and practitioner's guide[J]. Research synthesis methods, 2018, 9(4):602-614.
    [9] Wallace B C, Small K, Brodley C E, et al. Deploying an interactive machine learning system in an evidence-based practice center:abstrack[J]. ACM, 2012:819-824.
    [10] Park S E, Thomas J. Evidence synthesis software[J]. BMJ evidence-based medicine, 2018.
    [11] Gates A, Gates M, Sebastianski M, et al. The semi-automation of title and abstract screening:a retrospective exploration of ways to leverage Abstrackr's relevance predictions in systematic and rapid reviews[J]. BMC medical research methodology, 2020, 20(1):1-9.
    [12] Ouzzani M, Hammady H, Fedorowicz Z, et al. Rayyan-a web and mobile app for systematic reviews[J]. Systematic reviews, 2016, 5:1-10.
    [13] Przybyła P, Brockmeier A J, Kontonatsios G, et al. Prioritising references for systematic reviews with RobotAnalyst:a user study[J]. Research synthesis methods, 2018, 9(3):470-488.
    [14] Cheng S H, Augustin C, Bethel A,et al. Using machine learning to advance synthesis and use of conservation and environmental evidence[J]. Conservation Biology, 2018.
    [15] Van De Schoot R, De Bruin J, Schram R, et al. An open source machine learning framework for efficient and transparent systematic reviews[J]. Nature machine intelligence, 2021, 3(2):125-133.
    [16] 秦璇,刘佳利,王雨宁等.自然语言处理在系统评价中的应用[J].中国循证医学杂志,2021,21(6):715-720.
    [17] Cohen A M, Hersh W R, Peterson K, et al. Reducing workload in systematic review preparation using automated citation classification[J]. Journal of the American Medical Informatics Association, 2006, 13(2):206-219.
    [18] Gates A, Johnson C, Hartling L. Technology-assisted title and abstract screening for systematic reviews:a retrospective evaluation of the Abstrackr machine learning tool[J]. Systematic reviews, 2018, 7(1):1-9.
    [19] Tsou A Y, Treadwell J R, Erinoff E, et al. Machine learning for screening prioritization in systematic reviews:comparative performance of Abstrackr and EPPI-Reviewer[J]. Systematic reviews, 2020, 9:1-14.
    [20] Howard B E, Phillips J, Miller K, et al. SWIFT-Review:a text-mining workbench for systematic review[J]. Systematic reviews, 2016, 5:1-16.
    [21] 李世磊.基于文献相似度的系统评价引文筛选系统的设计与实现[D].电子科技大学,2020.
    [22] Marshall I J, Wallace B C. Toward systematic review automation:a practical guide to using machine learning tools in research synthesis[J]. Systematic reviews, 2019, 8:1-10.
    [23] Van Altena A J, Spijker R, Olabarriaga S D. Usage of automation tools in systematic reviews[J]. Research synthesis methods, 2019, 10(1):72-82.
    [24] 田宇.基于XML的WEB信息抽取系统研究与实现[D].内蒙古大学,2011.
    [25] 陈耀龙,罗旭飞,史乾灵等.人工智能如何改变指南的未来[J].协和医学杂志,2021,12(1):114-121.
    • Relative Articles(0)
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (87) PDF downloads(13) Cited by()
    Proportional views
    Related
    Links: National Health Commission of the People's Republic of China Chinese Academy of Medical Sciences(CAMS) AMLC Check CNKI Database CNKI Term Online Chinese General Practice
    Address：Room 302,Third Floor,Building 7, No. 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing 100730, China
    Tel：010-69154261/4262
    E - mail：medj@pumch.cn
    mjpumch@126.com
    Copyright of website：Editorial Office of Medical Journal of Peking Union Medical College Hospital

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return