Validation of a machine learning approach using FIB-4 and APRI scores assessed by the metavir scoring system: A cohort study.

Journal: Arab journal of gastroenterology : the official publication of the Pan-Arab Association of Gastroenterology
Published Date: Jun 1, 2021

Abstract

BACKGROUND AND STUDY AIM: The study aim was to improve and validate the accuracy of the fibrosis-4 (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI) scores for use in a potential machine-learning (ML) method that accurately predicts the extent of liver fibrosis.

Authors

  • Ahmed Hashem
    Endemic Medicine and Hepatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt.
  • Abubakr Awad
    School of Natural and Computing Sciences, University of Aberdeen, Aberdeen, UK.
  • Hend Shousha
    Endemic Medicine and Hepatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt. Electronic address: hendshousha@kasralainy.edu.eg.
  • Wafaa Alakel
    Endemic Medicine and Hepatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt; National Hepatology and Tropical Medicine Research Institute, Ministry of Health and Population, Cairo, Egypt.
  • Ahmed Salama
    Endemic Medicine and Hepatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt.
  • Tahany Awad
    Endemic Medicine and Hepatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt.
  • Mahasen Mabrouk
    Endemic Medicine Department, Faculty of Medicine, Cairo University.

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