Artificial intelligence in retinopathy of prematurity diagnosis

Brittni A. Scruggs, R. V. Paulchan, Jayashree Kalpathy-Cramer, Michael F. Chiang, J. Peter Campbell

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageEnglish (US)
Article number5
JournalTranslational Vision Science and Technology
Volume9
Issue number2
DOIs
StatePublished - Jan 1 2020

Keywords

  • Artificial intelligence
  • Machine learning
  • Pediatric retina
  • Retinopathy of prematurity

ASJC Scopus subject areas

  • Biomedical Engineering
  • Ophthalmology

Fingerprint Dive into the research topics of 'Artificial intelligence in retinopathy of prematurity diagnosis'. Together they form a unique fingerprint.

Cite this