Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning.

Journal: BMC medical informatics and decision making
Published Date: Jul 30, 2021

Abstract

BACKGROUND: Eligibility criteria are the primary strategy for screening the target participants of a clinical trial. Automated classification of clinical trial eligibility criteria text by using machine learning methods improves recruitment efficiency to reduce the cost of clinical research. However, existing methods suffer from poor classification performance due to the complexity and imbalance of eligibility criteria text data.

Authors

  • Kun Zeng
    College of Physical Science and Technology, Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, 361005, China.
  • Yibin Xu
    Research and Services Division of Materials Data and Integrated System (MaDIS), National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan.
  • Ge Lin
    National Engineering Research Center of Digital Life, Sun Yat-Sen University, Guangzhou, China.
  • Likeng Liang
    School of Computer Science, South China Normal University, Guangzhou, China.
  • Tianyong Hao
    School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou, China. haoty@gdufs.edu.cn.

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