A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach.

Journal: BMC medical informatics and decision making
Published Date: Nov 18, 2024

Abstract

BACKGROUND: Lung cancer is characterized by high morbidity and mortality due to the lack of practical early diagnostic and prognostic tools. The present study uses machine learning algorithms to construct a clinical predictive model for non-small cell lung cancer (NSCLC) patients.

Authors

  • Yuli Wang
    School of Control Science and Engineering, Shandong University, Jinan 250061, P.R.China.
  • Na Mei
    Clinical Medical Center of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
  • Ziyi Zhou
    Department of Otolaryngology Head and Neck Surgery，the Second Xiangya Hospital，Central South University，Changsha，410011，China.
  • Yuan Fang
    Department of Neurology, Dongyang People's Hospital, Affiliated to Wenzhou Medical University, Dongyang, China.
  • Jiacheng Lin
    Key Lab. of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang, China.
  • Fanchen Zhao
    School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.
  • Zhihong Fang
    Clinical Medical Center of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China. fangzhihong@shutcm.edu.cn.
  • Yan Li
    Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China.

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