Construction of an artificial neural network diagnostic model and investigation of immune cell infiltration characteristics for idiopathic pulmonary fibrosis.

Journal: BMC pulmonary medicine
Published Date: Sep 17, 2024

Abstract

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a severe lung condition, and finding better ways to diagnose and treat the disease is crucial for improving patient outcomes. Our study sought to develop an artificial neural network (ANN) model for IPF and determine the immune cell types that differed between the IPF and control groups.

Authors

  • Huizhe Zhang
    Department of Respiratory Medicine, Yancheng Hospital of Traditional Chinese Medicine; Yancheng TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Yancheng, Jiangsu, 224005, China.
  • Haibing Hua
    Department of Gastroenterology, Jiangyin Hospital of Traditional Chinese Medicine; Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangyin, Jiangsu, 214400, China.
  • Cong Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Chenjing Zhu
    State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, PR China.
  • Qingqing Xia
    Department of Pulmonary and Critical Care Medicine, Jiangyin Hospital of Traditional Chinese Medicine; Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangyin, Jiangsu, 214400, China.
  • Weilong Jiang
    Department of Pulmonary and Critical Care Medicine, Jiangyin Hospital of Traditional Chinese Medicine; Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangyin, Jiangsu, 214400, China. jwljytcm@163.com.
  • Xiaodong Hu
    Department of Pulmonary and Critical Care Medicine, Jiangyin Hospital of Traditional Chinese Medicine; Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangyin, Jiangsu, 214400, China. huxido2000@sina.com.
  • Yufeng Zhang

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