Artificial Intelligence in Retinopathy of Prematurity Diagnosis.

Journal: Translational vision science & technology
PMID: 32704411

Abstract

Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The diagnosis of ROP is subclassified by zone, stage, and plus disease, with each area demonstrating significant intra- and interexpert subjectivity and disagreement. In addition to improved efficiencies for ROP screening, artificial intelligence may lead to automated, quantifiable, and objective diagnosis in ROP. This review focuses on the development of artificial intelligence for automated diagnosis of plus disease in ROP and highlights the clinical and technical challenges of both the development and implementation of artificial intelligence in the real world.

Authors

  • Brittni A Scruggs
    Casey Eye Institute, Department of Ophthalmology, Oregon Health & Science University, Portland, OR, USA.
  • R V Paul Chan
    Ophthalmology, Illinois Eye and Ear Infirmary, Chicago, IL, United States.
  • Jayashree Kalpathy-Cramer
    Department of Radiology, MGH/Harvard Medical School, Charlestown, Massachusetts.
  • Michael F Chiang
    National Eye Institute, National Institutes of Health, Bethesda, Maryland.
  • J Peter Campbell
    Department of Ophthalmology, Oregon Health and Science University, Portland, Oregon.

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