Optical coherence tomography for identification of malignant pulmonary nodules based on random forest machine learning algorithm.

Journal: PloS one
Published Date: Dec 31, 2021

Abstract

OBJECTIVE: To explore the feasibility of using random forest (RF) machine learning algorithm in assessing normal and malignant peripheral pulmonary nodules based on in vivo endobronchial optical coherence tomography (EB-OCT).

Authors

  • Ming Ding
  • Shi-Yu Pan
    School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.
  • Jing Huang
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Cheng Yuan
    Department of Respiratory Medicine, Southeast University Zhongda Hospital, Nanjing, Jiangsu, China.
  • Qiang Zhang
    Yunan Provincial Center for Disease Control and Prevention, Kunming 650022, China.
  • Xiao-Li Zhu
    Department of Respiratory Medicine, Southeast University Zhongda Hospital, Nanjing, Jiangsu, China.
  • Yan Cai
    School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.

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