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The Real-World Impact of Artificial Intelligence on Diabetic Retinopathy Screening in Primary Care.

Authors
  • Cuadros, Jorge1, 2
  • 1 Meredith Morgan Eye Center, University of California, Berkeley, USA.
  • 2 EyePACS LLC, Santa Cruz, CA, USA.
Type
Published Article
Journal
Journal of Diabetes Science and Technology
Publisher
SAGE Publications
Publication Date
May 01, 2021
Volume
15
Issue
3
Pages
664–665
Identifiers
DOI: 10.1177/1932296820914287
PMID: 32329352
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

The study by Shah et al published in this issue of the Journal of Diabetes Science and Technology validates the IDx autonomous diabetic retinopathy (DR) screening program in a real-world setting. The study found high sensitivity (100%) but low specificity (82%) for referable DR. The resulting positive predictive value of 19% means that four out of five patients without referable DR would be referred to ophthalmology causing a significant burden to ophthalmologists, primary care clinics, and patients. Artificial intelligence programs that provide better specificity, multiple levels of DR, and annotations of where lesions are located in the retina may function better than a simple referral/no referral output. This will allow for better engagement of patients through the difficult process of adhering to treatment recommendations and control their diabetes.

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