Automation of literature screening using machine learning in medical evidence synthesis: a diagnostic test accuracy systematic review protocol.

Journal: Systematic reviews
Published Date: Jan 15, 2022

Abstract

BACKGROUND: Systematic review is an indispensable tool for optimal evidence collection and evaluation in evidence-based medicine. However, the explosive increase of the original literatures makes it difficult to accomplish critical appraisal and regular update. Artificial intelligence (AI) algorithms have been applied to automate the literature screening procedure in medical systematic reviews. In these studies, different algorithms were used and results with great variance were reported. It is therefore imperative to systematically review and analyse the developed automatic methods for literature screening and their effectiveness reported in current studies.

Authors

  • Yuelun Zhang
    Medical Research Center, PUMCH, CAMS & PUMC, Beijing, China.
  • Siyu Liang
    Department of Endocrinology, Endocrine Key Laboratory of Ministry of Health, PUMCH, CAMS & PUMC, 100730, Beijing, China.
  • Yunying Feng
    Eight-year Program of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Qing Wang
    School of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610500, China. qwang@163.com.
  • Feng Sun
    Department of Neurology, Brain Hospital Affiliated to Nanjing Medical University, Nanjing 210029, China.
  • Shi Chen
    Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, PUMCH, CAMS & PUMC, Beijing, China.
  • Yiying Yang
    Eight-year Program of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Xin He
    Department of Nephrology, The Affiliated Hospital of Guizhou Medical, Guizhou, China.
  • Huijuan Zhu
    Department of Endocrinology, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, Beijing, China.
  • Hui Pan
    Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, PUMCH, CAMS & PUMC, Beijing, China.

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