Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer.

Journal: Journal of integrative medicine
Published Date:

Abstract

OBJECTIVE: By optimizing the extreme learning machine network with particle swarm optimization, we established a syndrome classification and prediction model for primary liver cancer (PLC), classified and predicted the syndrome diagnosis of medical record data for PLC and compared and analyzed the prediction results with different algorithms and the clinical diagnosis results. This paper provides modern technical support for clinical diagnosis and treatment, and improves the objectivity, accuracy and rigor of the classification of traditional Chinese medicine (TCM) syndromes.

Authors

  • Liang Ding
    School of Computer, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, Jiangxi Province, China.
  • Xin-You Zhang
    School of Computer, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, Jiangxi Province, China. Electronic address: xinyouzhang@jxutcm.edu.cn.
  • Di-Yao Wu
    School of Pharmacy, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, Jiangxi Province, China.
  • Meng-Ling Liu
    School of Computer, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, Jiangxi Province, China.