Natural language processing was effective in assisting rapid title and abstract screening when updating systematic reviews.

Journal: Journal of clinical epidemiology
Published Date: Jan 21, 2021

Abstract

BACKGROUND AND OBJECTIVE: To examine whether the use of natural language processing (NLP) technology is effective in assisting rapid title and abstract screening when updating a systematic review.

Authors

  • Xuan Qin
    Chinese Evidence-based Medicine Center, Cochrane China Center and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
  • Jiali Liu
    Department of Clinical Oncology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.
  • Yuning Wang
    Clinical Department of Surgery, Chinese People's Liberation Army General Hospital (301 Hospital), 28 Fuxing Rd, 100853, Beijing, China.
  • Yanmei Liu
    Chinese Evidence-based Medicine Center, Cochrane China Center and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
  • Ke Deng
    Chinese Evidence-based Medicine Center, Cochrane China Center and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
  • Yu Ma
    Department of Electronic Engineering, Fudan University, Shanghai, China.
  • Kang Zou
    Chinese Evidence-based Medicine Center, Cochrane China Center and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
  • Ling Li
    College of Communication Engineering, Jilin University, Changchun, Jilin China.
  • Xin Sun
    Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA.

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