The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …
people. Accurate flood forecasts and control are essential to lessen these effects and …
Applications of deep learning in fundus images: A review
The use of fundus images for the early screening of eye diseases is of great clinical
importance. Due to its powerful performance, deep learning is becoming more and more …
importance. Due to its powerful performance, deep learning is becoming more and more …
CABNet: Category attention block for imbalanced diabetic retinopathy grading
Diabetic Retinopathy (DR) grading is challenging due to the presence of intra-class
variations, small lesions and imbalanced data distributions. The key for solving fine-grained …
variations, small lesions and imbalanced data distributions. The key for solving fine-grained …
Classification of diabetic retinopathy with feature selection over deep features using nature-inspired wrapper methods
M Canayaz - Applied Soft Computing, 2022 - Elsevier
Diabetic retinopathy (DR) is the most common cause of blindness in middle-aged people. It
shows that an automatic image evaluation system is needed in the diagnosis of this disease …
shows that an automatic image evaluation system is needed in the diagnosis of this disease …
[HTML][HTML] Deep learning for diabetic retinopathy detection and classification based on fundus images: A review
Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading
cause of blindness globally. Early detection and treatment are necessary in order to delay or …
cause of blindness globally. Early detection and treatment are necessary in order to delay or …
Deep learning-based automated detection for diabetic retinopathy and diabetic macular oedema in retinal fundus photographs
F Li, Y Wang, T Xu, L Dong, L Yan, M Jiang, X Zhang… - Eye, 2022 - nature.com
Objectives To present and validate a deep ensemble algorithm to detect diabetic retinopathy
(DR) and diabetic macular oedema (DMO) using retinal fundus images. Methods A total of …
(DR) and diabetic macular oedema (DMO) using retinal fundus images. Methods A total of …
Severity classification of diabetic retinopathy using an ensemble learning algorithm through analyzing retinal images
Diabetic Retinopathy (DR) refers to the damages endured by the retina as an effect of
diabetes. DR has become a severe health concern worldwide, as the number of diabetes …
diabetes. DR has become a severe health concern worldwide, as the number of diabetes …
A survey on the interpretability of deep learning in medical diagnosis
Deep learning has demonstrated remarkable performance in the medical domain, with
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
Deep learning for diabetic retinopathy analysis: a review, research challenges, and future directions
Deep learning (DL) enables the creation of computational models comprising multiple
processing layers that learn data representations at multiple levels of abstraction. In the …
processing layers that learn data representations at multiple levels of abstraction. In the …
Detection and classification of red lesions from retinal images for diabetic retinopathy detection using deep learning models
P Saranya, R Pranati, SS Patro - Multimedia Tools and Applications, 2023 - Springer
Diabetic retinopathy (DR) is an eye disease caused by retinal damage induced by the long-
term illness of diabetes mellitus. In the early stages, DR may show no symptoms or only …
term illness of diabetes mellitus. In the early stages, DR may show no symptoms or only …