Prediction of early hematoma expansion of spontaneous intracerebral hemorrhage based on deep learning radiomics features of noncontrast computed tomography.

Journal: European radiology
Published Date: May 1, 2024

Abstract

OBJECTIVES: Aimed to develop a nomogram model based on deep learning features and radiomics features for the prediction of early hematoma expansion.

Authors

  • Changfeng Feng
    Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, No. 261, Huansha Road, Hangzhou, Zhejiang, China.
  • Zhongxiang Ding
  • Qun Lao
    Department of Radiology, Hangzhou Children's Hospital, Hangzhou, Zhejiang, China.
  • Tao Zhen
    Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, No. 261, Huansha Road, Hangzhou, Zhejiang, China.
  • Mei Ruan
    Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, No. 261, Huansha Road, Hangzhou, Zhejiang, China.
  • Jing Han
    Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education; School of Pharmaceutical Sciences, Wuhan University, Wuhan 430071, China.
  • Linyang He
    Hangzhou Jianpei Technology Co., Ltd, Hangzhou, China.
  • Qijun Shen
    Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, No. 261, Huansha Road, Hangzhou, Zhejiang, China. shenqijun80@163.com.

Keywords

External Resources

Popular Topics
Recent Journals