Structural analysis and intelligent classification of clinical trial eligibility criteria based on deep learning and medical text mining.

Journal: Journal of biomedical informatics
PMID: 39603550

Abstract

OBJECTIVE: To enhance the efficiency, quality, and innovation capability of clinical trials, this paper introduces a novel model called CTEC-AC (Clinical Trial Eligibility Criteria Automatic Classification), aimed at structuring clinical trial eligibility criteria into computationally explainable classifications.

Authors

  • Yongzhong Han
    School of Electronic and Electric Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China.
  • Qianmin Su
    Department of Computer Science, School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, No. 333 Longteng Road, Shanghai, 201620, China. suqm@sues.edu.cn.
  • Liang Liu
    College of Cybersecurity, Sichuan University, Chengdu, China.
  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Jihan Huang
    Center for Drug Clinical Research, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.

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