Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population.

Journal: Journal of translational medicine
Published Date: Mar 31, 2020

Abstract

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major public health problem and cause of mortality worldwide. However, COPD in the early stage is usually not recognized and diagnosed. It is necessary to establish a risk model to predict COPD development.

Authors

  • Xia Ma
    Department of Pulmonary and Critical Care Medicine, General Hospital of Datong Coal Mine Group Co., Ltd., Datong, 037000, China.
  • Yanping Wu
    Department of Biomedical Engineering, School of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
  • Ling Zhang
  • Weilan Yuan
    Shanghai Biotecan Pharmaceuticals Co., Ltd., 180 Zhangheng Road, Shanghai, 201204, China.
  • Li Yan
    Wenzhou Public Utilities Investment Group Co. Ltd., Wenzhou 325000, China. Electronic address: Vangji@126.com.
  • Sha Fan
    Department of Respiratory Medicine, Heji Hospital Affiliated with Changzhi Medical College, Changzhi, 046011, China.
  • Yunzhi Lian
    Department of Clinical Laboratory, JinCheng People's Hospital, Jincheng, 048000, China.
  • Xia Zhu
    Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510060, China.
  • Junhui Gao
    Shanghai Biotecan Pharmaceuticals Co., Ltd., 180 Zhangheng Road, Shanghai, 201204, China.
  • Jiangman Zhao
    Shanghai Biotecan Pharmaceuticals Co., Ltd., 180 Zhangheng Road, Shanghai, 201204, China.
  • Ping Zhang
    Department of Computer Science and Engineering, The Ohio State University, USA.
  • Hui Tang
    Department of Pharmacy, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
  • Weihua Jia
    Department of Respiratory, General Hospital of Tisco (Sixth Hospital of Shanxi Medical University), 2 Yingxin Street, Jiancaoping District, Taiyuan, 030008, Shanxi Province, China. 1051569807@qq.com.

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