Multicenter, Head-to-Head, Real-World Validation Study of Seven Automated Artificial Intelligence Diabetic Retinopathy Screening Systems. Diabetes Care 2021;44:XXXX-XXXX

Diabetes Care. 2021 May;44(5):e108-e109. doi: 10.2337/dci21-0007.

Authors

Aaron Y Lee^{1

2

3}, Cecilia S Lee^{4

2}, Matthew S Hunt⁴, Ryan T Yanagihara⁴, Marian Blazes⁴, Edward J Boyko^{5

6}

Affiliations

¹ Department of Ophthalmology, University of Washington School of Medicine, Seattle, WA leeay@uw.edu.
² Department of Ophthalmology, Puget Sound Veteran Affairs, Seattle, WA.
³ eScience Institute, University of Washington, Seattle, WA.
⁴ Department of Ophthalmology, University of Washington School of Medicine, Seattle, WA.
⁵ Seattle Epidemiologic Research and Information Center, Department of Veteran Affairs Medical Center, Seattle, WA.
⁶ Department of Medicine, University of Washington, Seattle, WA.

No abstract available

Publication types

Letter
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, P.H.S.
Comment

MeSH terms

Artificial Intelligence
Diabetes Mellitus*
Diabetic Retinopathy* / diagnosis
Humans
Mass Screening

Grants and funding