Utilization of artificial intelligence approach for prediction of DLP values for abdominal CT scans: A high accuracy estimation for risk assessment.

Journal: Frontiers in public health
Published Date: Jul 28, 2022

Abstract

PURPOSE: This study aimed to evaluate Artificial Neural Network (ANN) modeling to estimate the significant dose length product (DLP) value during the abdominal CT examinations for quality assurance in a retrospective, cross-sectional study.

Authors

  • H O Tekin
    Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates.
  • Faisal Almisned
    Department Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.
  • T T Erguzel
    Department of Software Engineering, Faculty of Engineering and Natural Sciences, Uskudar University, Istanbul, Turkey.
  • Mohamed M Abuzaid
    Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah, UAE. Electronic address: mabdelfatah@sharjah.ac.ae.
  • W Elshami
    Department of Medical Diagnostic Imaging, College of Health Sciences, University of Sharjah, United Arab Emirates. Electronic address: welshami@sharjah.ac.ae.
  • Antoaneta Ene
    Department of Chemistry, Physics and Environment, Faculty of Sciences and Environment, INPOLDE Research Center, Dunarea de Jos University of Galati, Galati, Romania.
  • Shams A M Issa
    Physics Department, Faculty of Science, Al-Azhar University, Assiut, Egypt.
  • Hesham M H Zakaly
    Physics Department, Faculty of Science, Al-Azhar University, Assiut, Egypt.

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