Machine Learning Methods Based on Chest CT for Predicting the Risk of COVID-19-Associated Pulmonary Aspergillosis.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: To develop and validate a machine learning model based on chest CT and clinical risk factors to predict secondary aspergillus infection in hospitalized COVID-19 patients.

Authors

  • Jiahao Liu
    School of Artificial Intelligence, Hebei University of Technology, Tianjin, 300130, China.
  • Juntao Zhang
    GE Healthcare PDX GMS Medical Affairs, Shanghai, China (J.Z.).
  • Huaizhen Wang
    Department of Radiology, The First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
  • Caiyun Fang
    Department of Radiology, Guang'anmen Hospital Jinan Hospital, Jinan, China (C.F.).
  • Lingzhen Wei
    Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China; School of Clinical Medicine, Jining Medical University, Jining, Shandong, China.
  • Jinming Chen
    Department of Radiology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, Shandong, China.
  • Meilin Li
    Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China.
  • Shuzhen Wu
    Shandong First Medical University, Jinan, China (J.L., M.L., S.W.); Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China (S.W.).
  • Qingshi Zeng
    Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.