Autonomous Artificial Intelligence for Diabetic Eye Disease Testing Improves Access and Equity in the Pediatric and Adult Populations: The Johns Hopkins Medicine Experience

This article discusses the implementation and impact of autonomous artificial intelligence (AI) systems for diabetic eye disease testing at the Johns Hopkins Medicine health system, highlighting improvements in screening rates, access to care, and health equity for underserved populations. The AI technology has been effective in both adult and pediatric populations and has reduced disparities and increased follow-up with eye care professionals. While considering the challenges and successes of this approach, this article also highlights the potential long-term impact of AI systems in improving visual health outcomes for people with diabetes in diverse health care settings.

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Publication Details

Journal
Diabetes Spectrum
Published
2025-02-01
DOI
https://doi.org/10.2337/dsi24-0016
Citations
1
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
1.36
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article

Autonomous Artificial Intelligence for Diabetic Eye Disease Testing Improves Access and Equity in the Pediatric and Adult Populations: The Johns Hopkins Medicine Experience

T. Y. Alvin Liu, Risa M. Wolf
1 citations
Diabetes Spectrum
Retinal Imaging and Analysis
1.36
article

Autonomous Artificial Intelligence for Diabetic Eye Disease Testing Improves Access and Equity in the Pediatric and Adult Populations: The Johns Hopkins Medicine Experience

T. Y. Alvin Liu, Risa M. Wolf
article en
1 citations

Abstract

This article discusses the implementation and impact of autonomous artificial intelligence (AI) systems for diabetic eye disease testing at the Johns Hopkins Medicine health system, highlighting improvements in screening rates, access to care, and health equity for underserved populations. The AI technology has been effective in both adult and pediatric populations and has reduced disparities and increased follow-up with eye care professionals. While considering the challenges and successes of this approach, this article also highlights the potential long-term impact of AI systems in improving visual health outcomes for people with diabetes in diverse health care settings.

Diabetes SpectrumVol. 38(1)
Johns Hopkins University (US), Johns Hopkins Medicine (US)
Openalex Percentile: Top 24%
Retinal Imaging and Analysis
1.36
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Autonomous Artificial Intelligence for Diabetic Eye Disease Testing Improves Access and Equity in the Pediatric and Adult Populations: The Johns Hopkins Medicine Experience — T. Y. Alvin Liu, Risa M. Wolf · Diabetes Spectrum (2025) | TGRS Research Map | TGRS