Leveraging Semi-Supervised Graph Learning for Enhanced Diabetic Retinopathy Detection

D Dhinakaran, L Srinivasan, D Selvaraj… - arXiv preprint arXiv …, 2023 - arxiv.org
Diabetic Retinopathy (DR) is a significant cause of blindness globally, highlighting the
urgent need for early detection and effective treatment. Recent advancements in Machine …

Semi-supervised auto-encoder graph network for diabetic retinopathy grading

Y Li, Z Song, S Kang, S Jung, W Kang - IEEE Access, 2021 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) causes quite a few blindness worldwide, which can be refrained
by the timely diagnosis on retinal images. Recently, researches on deep learning-based …

Hybrid graph convolutional network for semi-supervised retinal image classification

G Zhang, J Pan, Z Zhang, H Zhang, C Xing… - IEEE …, 2021 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) causes a significant health threat to the patient's vision with
diabetic disease, which may result in blindness in severe situations. Various automatic DR …

[HTML][HTML] Dynamic graph clustering learning for unsupervised diabetic retinopathy classification

C Yu, H Pei - Diagnostics, 2023 - mdpi.com
Diabetic retinopathy (DR) is a common complication of diabetes, which can lead to vision
loss. Early diagnosis is crucial to prevent the progression of DR. In recent years, deep …

Transfer learning based detection of diabetic retinopathy from small dataset

MT Hagos, S Kant - arXiv preprint arXiv:1905.07203, 2019 - arxiv.org
Annotated training data insufficiency remains to be one of the challenges of applying deep
learning in medical data classification problems. Transfer learning from an already trained …

[HTML][HTML] Diabetic retinopathy grading by deep graph correlation network on retinal images without manual annotations

G Zhang, B Sun, Z Chen, Y Gao, Z Zhang, K Li… - Frontiers in …, 2022 - frontiersin.org
Background Diabetic retinopathy, as a severe public health problem associated with vision
loss, should be diagnosed early using an accurate screening tool. While many previous …

Multi-point attention-based semi-supervised learning for diabetic retinopathy classification

C Zhang, P Chen, T Lei - Biomedical Signal Processing and Control, 2023 - Elsevier
In recent years, the severity classification of some well-known diseases has gradually
become a focus of researchers, especially diabetic retinopathy (DR) recognition caused by …

Graph adversarial transfer learning for diabetic retinopathy classification

J Hu, H Wang, L Wang, Y Lu - IEEE Access, 2022 - ieeexplore.ieee.org
Diabetic retinopathy (DR) is an essential factor that has caused vision loss and even
blindness in middle-aged and older adults. A system that can automatically perform DR …

Automatic detection of diabetic retinopathy: a review on datasets, methods and evaluation metrics

M Mateen, J Wen, M Hassan, N Nasrullah, S Sun… - IEEE …, 2020 - ieeexplore.ieee.org
Diabetic retinopathy (DR) is a fast-spreading disease across the globe, which is caused by
diabetes. The DR may lead the diabetic patients to complete vision loss. In this scenario …

[HTML][HTML] Deep and densely connected networks for classification of diabetic retinopathy

H Riaz, J Park, H Choi, H Kim, J Kim - Diagnostics, 2020 - mdpi.com
Diabetes has recently emerged as a worldwide problem, and diabetic retinopathy is an
abnormal state associated with the human retina. Due to the increase in daily screen-related …