… complications such as diabetic retinopathy and macular edema in the human eye retina,
the … detection using deep learning technique. Here we present a deep learning system that …

… To assess reliability of the deep learning algorithm we compared the Dice coefficients for
deep learning automated segmentations against manual segmentations by four independent …

… grading fundus images, deep-learning algorithms are able to … We hypothesized that deep
learning could be leveraged to … two independent datasets, using deep learning. In addition, the …

… macular edema. Herein, we developed a novel deep learning model for the segmentation of
macular edema … pooling (ASPP) to detect macular edema at multiple features and used the …

… , we construct a deep learning-based risk classification model for diabetic macular edema.
With a … -to-learn classes was improved by image enhancement of the data, cosine annealing …

… deep learning model was developed to detect different morphological patterns of diabetic
macular edema … personalized therapeutic strategies for patients with diabetic macular edema. …

… using deep learning approaches. Deep learning methods have mostly been used for high
classification and object detection of images. One of the most well known deep convolutional …

… This study aims at identifying macular edema on OCT images using a lightweight explainable
CNN architecture by composing significant feature activation maps and reducing the …

… Diabetic macular edema (DME) is a kind of hard exudates lesion seen near the diabetic
macular region of the retina. DME causes visual loss and may result in complete blindness; …

Anti-vascular endothelial growth factor (VEGF) agents are widely regarded as the first line of
therapy for diabetic macular edema (DME) but are not universally effective. An automatic …