FMDNN: A Fuzzy-guided Multi-granular Deep Neural Network for Histopathological Image Classification
W Ding, T Zhou, J Huang, S Jiang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Histopathological image classification constitutes a pivotal task in computer-aided
diagnostics. The precise identification and categorization of histopathological images are of …
diagnostics. The precise identification and categorization of histopathological images are of …
Improving brain tumor classification with combined convolutional neural networks and transfer learning
Brain tumors pose a serious threat, causing the deaths of thousands of people worldwide,
and can lead to life-threatening consequences when not accurately diagnosed. The …
and can lead to life-threatening consequences when not accurately diagnosed. The …
[HTML][HTML] A hybrid approach with customized machine learning classifiers and multiple feature extractors for enhancing diabetic retinopathy detection
Diabetic retinopathy (DR) is a severe global issue causing blindness if untreated, affecting
millions worldwide and worsening over time. Addressing this growing concern necessitates …
millions worldwide and worsening over time. Addressing this growing concern necessitates …
Detecting diabetic retinopathy using a hybrid ensemble XL machine model with dual weighted-Kernel ELM and improved mayfly optimization
A Kannan, SP Palanivel, SR Karthikeyan… - Expert Systems with …, 2024 - Elsevier
The uncontrolled increase of blood glucose level affects the retina and cause Diabetic
Retinopathy (DR), which can permanently damage blood vessels if left untreated for a long …
Retinopathy (DR), which can permanently damage blood vessels if left untreated for a long …
Automated diabetic retinopathy screening using deep learning
S Guefrachi, A Echtioui, H Hamam - Multimedia Tools and Applications, 2024 - Springer
The purpose of this research is to propose a new method for identifying diabetic retinopathy
using retinal fundus images. Currently, identifying diabetic retinopathy from computerized …
using retinal fundus images. Currently, identifying diabetic retinopathy from computerized …
Diabetic Retinopathy Detection Using Deep Learning Multistage Training Method
S Guefrachi, A Echtioui, H Hamam - Arabian Journal for Science and …, 2024 - Springer
Diabetic retinopathy (DR) stands as the most prevalent diabetic eye ailment and constitutes
one of the primary causes of blindness worldwide. Detecting and classifying retinal images …
one of the primary causes of blindness worldwide. Detecting and classifying retinal images …
Two-Stage Deep Learning Model for Diagnosis of Lumbar Spondylolisthesis Based on Lateral X-Ray Images
C Xu, X Liu, B Bao, C Liu, R Li, T Yang, Y Wu… - World Neurosurgery, 2024 - Elsevier
Background Diagnosing early lumbar spondylolisthesis is challenging for many doctors
because of the lack of obvious symptoms. Using deep learning (DL) models to improve the …
because of the lack of obvious symptoms. Using deep learning (DL) models to improve the …
EASM: An efficient AttnSleep model for sleep Apnea detection from EEG signals
This paper addresses the crucial task of automatic sleep stage classification to assist sleep
experts in diagnosing sleep disorders such as sleep apnea and insomnia. The proposed …
experts in diagnosing sleep disorders such as sleep apnea and insomnia. The proposed …
Bio-inspired Approach for Early Diabetes Prediction and Diet Recommendation
Diabetes mellitus is one of the hyperglycemic diseases. To meet with an objective of early
prediction of diabetes, the paper comprises of case studies of diabetes patients, the existing …
prediction of diabetes, the paper comprises of case studies of diabetes patients, the existing …
Exploration of AI-powered DenseNet121 for effective diabetic retinopathy detection
KS Lakshmi, B Sargunam - International Ophthalmology, 2024 - Springer
Abstract Objective Diabetic Retinopathy (DR) is a severe complication of diabetes that
damages the retina and affects approximately 80% of patients with diabetes for 10 years or …
damages the retina and affects approximately 80% of patients with diabetes for 10 years or …