Prediction of proliferative diabetic retinopathy using machine learning in Latino and non-Hispanic black cohorts with routine blood and urine testing.

Journal: Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
Published Date: Jul 12, 2024

Abstract

PURPOSE: The objective was to predict proliferative diabetic retinopathy (PDR) in non-Hispanic Black (NHB) and Latino (LA) patients by applying machine learning algorithms to routinely collected blood and urine laboratory results.

Authors

  • Ayelet Goldstein
    Medical Informatics Research Center, Department of Information Systems Engineering, Ben Gurion University of the Negev, Beer Sheva, Israel.
  • Kun Ding
    The Sixty-Third Research Institute, National University of Defense Technology, Nanjing, 210007, China; Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, 410073, China. Electronic address: dingkun18@nudt.edu.cn.
  • Onelys Carasquillo
    Department of Ophthalmology, Bronxcare Health Center, Bronx, New York, USA.
  • Barton Levine
    Department of Nephrology, West Los Angeles VA Medical Center, Los Angeles, California, USA.
  • Aisha Hasan
    Department of Ophthalmology, Bronxcare Health Center, Bronx, New York, USA.
  • Jonathan Levine
    Texas A&M University College of Veterinary Medicine and Biomedical Sciences, College Station, Texas, USA.

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