Endobronchial Ultrasound-Based Support Vector Machine Model for Differentiating between Benign and Malignant Mediastinal and Hilar Lymph Nodes.

Journal: Respiration; international review of thoracic diseases
PMID:

Abstract

INTRODUCTION: The aim of the study was to establish an ultrasonographic radiomics machine learning model based on endobronchial ultrasound (EBUS) to assist in diagnosing benign and malignant mediastinal and hilar lymph nodes (LNs).

Authors

  • Wenjia Hu
    Department of Ultrasound, Zhengzhou University People's Hospital, Zhengzhou, China.
  • Feifei Wen
    Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, China, wfei0811@163.com.
  • Mengyu Zhao
    Department of Respiratory and Critical Care Medicine, Henan Provincial People's Hospital, Zhengzhou, China.
  • Xiangnan Li
    1 The Nursing College of Zhengzhou University, Zhengzhou 450052, China ; 2 Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
  • Peiyuan Luo
    Department of Respiratory and Critical Care Medicine, Henan Provincial People's Hospital, Zhengzhou, China.
  • Guancheng Jiang
    Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, China.
  • Huizhen Yang
    School of Electric Engineering, Jiangsu Ocean University, Lianyungang, 222005, China.
  • Felix J F Herth
    Department of Pulmonology and Critical Care Medicine, Thoraxklinik at the University of Heidelberg, Heidelberg, Germany.
  • Xiaoju Zhang
    Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, China.
  • Quncheng Zhang
    Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, China.