Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics.

Journal: BMC medical imaging
PMID: 39164667

Abstract

BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predicting the diagnosis of Non-Alcoholic Steatohepatitis.

Authors

  • Fei Xia
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA.
  • Wei Wei
    Dept. Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
  • Junli Wang
    Key Laboratory of Embedded System and Service Computing (Tongji University), Ministry of Education, Shanghai 201804, China.
  • Yayang Duan
    Department of Ultrasound, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Kun Wang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Chaoxue Zhang
    Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

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