Post

New research · Ophthalmology
Frontiers in endocrinology · 4d
AI / informaticsFrontiers in endocrinology · 2026

Diagnostic accuracy and clinical performance of deep learning models for grading diabetic retinopathy: a systematic review and meta-analysis.

Xin Yan, Shiqi Lei, Lifen Hu … Na Wu
Read paper
OphthalmologyAI / informatics

Deep learning detects no diabetic retinopathy with very high sensitivity on fundus photos

Diagnostic accuracy and clinical performance of deep learning models for grading diabetic retinopathy: a systematic review and meta-analysis.

Xin Yan … Na Wu
Frontiers in endocrinology · 2026
Background

Diabetic retinopathy (diabetic retinopathy) is a leading cause of preventable visual impairment worldwide, and its precise severity grading is critical for optimizing clinical management.

Purpose

This systematic review and meta-analysis aimed to comprehensively assess the diagnostic accuracy of fundus image-based deep learning models in the grading of diabetic retinopathy.

Methods

PubMed, Embase, Web of Science, and the Cochrane Library were systematically searched for relevant studies published up to October 28, 2025.

n = 41 studies
Results

correctly flags nearly all eyes that truly have no diabetic retinopathy

No DR (stage 0)
95.19%
Mild NPDR (stage 1)
72.06%
Moderate NPDR (stage 2
84.33%
Severe NPDR (stage 3)
75.84%
More results

In the simplified four-class classification task, sensitivities markedly improved across all grades: 96.85% (95% CI: 90.18%-99.93%) for stage 0, 92.94% (95% CI: 79.50%-99.72%) for stage 1, 92.75% (95% CI: 79.31%-99.61%) for stage 2, and 88.19% (95% CI: 68.99%-98.93%) for stage 3.

“
Conclusion · 1 of 3

Deep learning exhibits high sensitivity and substantial potential for diabetic retinopathy grading, particularly in screening for no diabetic retinopathy and vision-threatening diabetic retinopathy.

Conclusion · 2 of 3

Nevertheless, precisely differentiating between adjacent non-proliferative stages remains a clinical challenge.

Conclusion · 3 of 3

The observed heterogeneity underscores the imperative for methodological standardization, rigorous external validation, and multimodal data integration.

Read paper
0 comments

No comments yet. Be the first.

Related papers

LatestFoundational
Cross-sectional
44.1%
had too much homocysteine in the blood, a far larger share than in dry AMD or healthy eyes
Cohort Study
92.3%
most laser-treated eyes had a favorable eye-structure outcome
Cohort Study
56%
lost three or more lines on the eye-chart vision test
Cohort Study
50%
older patients were more likely to lose three or more lines of vision
Study
81%
trials where mask air leaks were detected blowing toward the eyes
Cohort Study
13.5%
Central retinal artery peak blood-flow speed was 13.5% lower in diabetic patients.
Study
379 +/- 156 microm
lower thickness in the central retina, checked with an eye scan
Case Report
9 of 10 eyes
eyes had better measured vision after treatment