Development and validation of machine learning classifiers for predicting treatment-needed retinopathy of prematurity.

Journal: BMC medical informatics and decision making
Published Date: Jul 1, 2025

Abstract

BACKGROUND: This study aims to design and evaluate various supervised machine-learning models for identifying premature infants who require treatment based on demographic data and clinical findings from screening examinations.

Authors

  • Nasser Shoeibi
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Majid Abrishami
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Seyedeh Maryam Hosseini
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Mohammad-Reza Ansari-Astaneh
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Razieh Farrahi
    Department of Health Information Technology, Ferdows Faculty of Medical Sciences, Birjand, Iran.
  • Bahareh Gharib
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Fatemeh Neghabi
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Mojtaba Abrishami
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Mehdi Sakhaee
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Mehrdad Motamed Shariati
    Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. Mehrdad_shariati2005@yahoo.com.

Keywords

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