External validation study on the value of deep learning algorithm for the prediction of hematoma expansion from noncontrast CT scans.

Journal: BMC medical imaging
Published Date: Mar 14, 2022

Abstract

BACKGROUND: Hematoma expansion is an independent predictor of patient outcome and mortality. The early diagnosis of hematoma expansion is crucial for selecting clinical treatment options. This study aims to explore the value of a deep learning algorithm for the prediction of hematoma expansion from non-contrast computed tomography (NCCT) scan through external validation.

Authors

  • Dong Chuang Guo
    Department of Radiology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, Zhejiang Province, China.
  • Jun Gu
    School of Computer Science and Technology, Department of Telecommunications, Xi'an Jiaotong University, Xi'an, China.
  • Jian He
    School of Software Engineering, Beijing University of Technology, Beijing, China. Electronic address: jianhee@bjut.edu.cn.
  • Hai Rui Chu
    Department of Radiology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, Zhejiang Province, China.
  • Na Dong
    School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin, China. dongna@tju.edu.cn.
  • Yi Feng Zheng
    Department of Radiology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, Zhejiang Province, China. 2506861828@qq.com.

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