Post

New research · Ophthalmology
Frontiers in artificial intelligence · 5d
StudyFrontiers in artificial intelligence · 2026

Fusion of ConvNeXt-Tiny and Swin-Tiny backbones: a comparative analysis for diabetic retinopathy classification.

J Paranthaman, Sathya Pichandi, Aparna Mohanty
Read paper
OphthalmologyStudy

A fusion model accurately classified diabetic retinopathy with 88.34% mean test accuracy.

Fusion of ConvNeXt-Tiny and Swin-Tiny backbones: a comparative analysis for diabetic retinopathy classification.

J Paranthaman … Aparna Mohanty
Frontiers in artificial intelligence · 2026
Background

Diabetic retinopathy (diabetic retinopathy) is a leading cause of preventable blindness, which has motivated the development of reliable automated grading systems on retinal fundus images.

Results
88.34%
the computer model correctly identified diabetic eye disease in this percentage of cases
More results

In this study, we perform a controlled comparative evaluation of ConvNeXt-Tiny, Swin-Tiny and their feature fusion for diabetic retinopathy classification using the Asia Pacific Tele-Ophthalmology Society (Asia Pacific Tele-Ophthalmology Society) 2019 dataset.

More results

All models were initialized with weights pre-trained on ImageNet-1K and evaluated with two transfer learning strategies: direct fine-tuning on Asia Pacific Tele-Ophthalmology Society 2019, and EyePACS-based domain adaptation with task-specific fine-tuning.

“
Conclusion

The study also emphasizes the importance of controlled comparative evaluation, stability analysis, and configuration-specific evaluation in the research of medical image classification.

Read paper
0 comments

No comments yet. Be the first.

Related papers

LatestFoundational
AI / Informatics
0·962 for OCT
MerMED-FM was very accurate at diagnosing diseases using eye scans
AI / Informatics
0.98
Artificial intelligence's eyelid-height measurements matched doctors' manual measurements almost perfectly
AI / Informatics
92.1%
combining eye scans and photos correctly told benign from cancerous lesions apart nearly every time
Cohort Study
28.6%
recurred locally in more than 1 in 4 patients over years of follow-up
Cohort Study
-0.395
excision group's post-op eyelid fullness score was lower - greater improvement
Cohort Study
86.7%
of infants probed after 12 months still had unresolved tear duct blockage
Observational
16%
eyelid tissue in rosacea patients showed less of this key repair-signaling protein inside cell nuclei
Cohort Study
25%
about 1 in 4 treated cases had symptoms return after improving