Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005-2023).

Journal: Computer methods and programs in biomedicine
Published Date: Nov 22, 2023

Abstract

BACKGROUND AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is a common liver disease with a rapidly growing incidence worldwide. For prognostication and therapeutic decisions, it is important to distinguish the pathological stages of NAFLD: steatosis, steatohepatitis, and liver fibrosis, which are definitively diagnosed on invasive biopsy. Non-invasive ultrasound (US) imaging, including US elastography technique, and clinical parameters can be used to diagnose and grade NAFLD and its complications. Artificial intelligence (AI) is increasingly being harnessed for developing NAFLD diagnostic models based on clinical, biomarker, or imaging data. In this work, we systemically reviewed the literature for AI-enabled NAFLD diagnostic models based on US (including elastography) and clinical (including serological) data.

Authors

  • H Zamanian
    Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • A Shalbaf
    Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: shalbaf@sbmu.ac.ir.
  • M R Zali
    Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • A R Khalaj
    Tehran obesity treatment center, Department of Surgery, Faculty of Medicine, Shahed University, Tehran, Iran.
  • P Dehghan
    Department of Radiology, Imaging Department, Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • M Tabesh
    Cardiac Primary Prevention Research Center, Cardiovascular Diseases Research, Tehran University of Medical Sciences, Tehran, Iran.
  • B Hatami
    Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • R Alizadehsani
    Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, VIC 3216, Australia.
  • Ru-San Tan
    National Heart Centre Singapore, Singapore, Singapore.
  • U Rajendra Acharya
    School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Darling Heights, Australia.

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