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A survey on deep-learning-based diabetic retinopathy classification
The number of people who suffer from diabetes in the world has been considerably
increasing recently. It affects people of all ages. People who have had diabetes for a long …
increasing recently. It affects people of all ages. People who have had diabetes for a long …
Classification and segmentation of diabetic retinopathy: a systemic review
Diabetic retinopathy (DR) is a major reason of blindness around the world. The
ophthalmologist manually analyzes the morphological alterations in veins of retina, and …
ophthalmologist manually analyzes the morphological alterations in veins of retina, and …
[HTML][HTML] Overcoming nonlinear dynamics in diabetic retinopathy classification: a robust AI-based model with chaotic swarm intelligence optimization and recurrent long …
Diabetic retinopathy (DR), which is seen in approximately one-third of diabetes patients
worldwide, leads to irreversible vision loss and even blindness if not diagnosed and treated …
worldwide, leads to irreversible vision loss and even blindness if not diagnosed and treated …
Skin lesion classification of dermoscopic images using machine learning and convolutional neural network
Detecting dangerous illnesses connected to the skin organ, particularly malignancy,
requires the identification of pigmented skin lesions. Image detection techniques and …
requires the identification of pigmented skin lesions. Image detection techniques and …
[HTML][HTML] CNN-hyperparameter optimization for diabetic maculopathy diagnosis in optical coherence tomography and fundus retinography
Diabetic Maculopathy (DM) is considered the most common cause of permanent visual
impairment in diabetic patients. The absence of clear pathological symptoms of DM hinders …
impairment in diabetic patients. The absence of clear pathological symptoms of DM hinders …
Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine‐Tuning Approach
Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most
important tasks for neurologists and radiologists is to detect brain tumors early. Recent …
important tasks for neurologists and radiologists is to detect brain tumors early. Recent …
A novel fusion of genetic grey wolf optimization and kernel extreme learning machines for precise diabetic eye disease classification
In response to the growing number of diabetes cases worldwide, Our study addresses the
escalating issue of diabetic eye disease (DED), a significant contributor to vision loss …
escalating issue of diabetic eye disease (DED), a significant contributor to vision loss …
Smart detection and diagnosis of diabetic retinopathy using bat based feature selection algorithm and deep forest technique
P Modi, Y Kumar - Computers & Industrial Engineering, 2023 - Elsevier
Diabetic retinopathy is a retinal eye disease due to presence of diabetes and diabetes can
be described as metabolic disorder in which glucose level is higher in human body. Diabetic …
be described as metabolic disorder in which glucose level is higher in human body. Diabetic …
Diabetic retinopathy detection and severity classification using optimized deep learning with explainable AI technique
Diabetic Retinopathy (DR) is a serious consequence of prolonged diabetic patients that
causes vision threatening issues and irreversible blindness problem. In the beginning stage …
causes vision threatening issues and irreversible blindness problem. In the beginning stage …
Deep learning-enhanced diabetic retinopathy image classification
Objective Diabetic retinopathy (DR) can sometimes be treated and prevented from causing
irreversible vision loss if caught and treated properly. In this work, a deep learning (DL) …
irreversible vision loss if caught and treated properly. In this work, a deep learning (DL) …