Application of artificial intelligence for classification, segmentation, early detection, early diagnosis, and grading of diabetic retinopathy from fundus retinal images: A …
G Rajarajeshwari, GC Selvi - IEEE Access, 2024 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) remains a major factor contributing to vision loss worldwide,
particularly among individuals with diabetes. Timely and accurate diagnosis of DR is …
particularly among individuals with diabetes. Timely and accurate diagnosis of DR is …
Diabetic retinopathy detection and grading: A transfer learning approach using simultaneous parameter optimization and feature-weighted ECOC ensemble
Early detection of Diabetic Retinopathy (DR) is crucial as it may cause blindness. Manual
diagnosis of DR severity by ophthalmologists is challenging and time consuming. Therefore …
diagnosis of DR severity by ophthalmologists is challenging and time consuming. Therefore …
Transfer learning in brain tumor classification: challenges, opportunities, and future prospects
Brain tumor classification plays a critical role in diagnosing and treating patients effectively.
However, the limited availability of annotated data and the complexity of tumor images …
However, the limited availability of annotated data and the complexity of tumor images …
Transfer learning for diabetic retinopathy detection: a study of dataset combination and model performance
AM Mutawa, S Alnajdi, S Sruthi - Applied Sciences, 2023 - mdpi.com
Diabetes' serious complication, diabetic retinopathy (DR), which can potentially be life-
threatening, might result in vision loss in certain situations. Although it has no symptoms in …
threatening, might result in vision loss in certain situations. Although it has no symptoms in …
A hybrid evolutionary weighted ensemble of deep transfer learning models for retinal vessel segmentation and diabetic retinopathy detection
Segmentation of retinal blood vessels in fundus images is critical for early detection and
treatment of diabetic retinopathy (DR). Due to the complex distribution of blood vessels …
treatment of diabetic retinopathy (DR). Due to the complex distribution of blood vessels …
GNN-fused CapsNet with multi-head prediction for diabetic retinopathy grading
Diabetic retinopathy (DR) is a prevalent complication of diabetes, affecting a substantial
number of individuals worldwide and being a leading cause of blindness. The accurate and …
number of individuals worldwide and being a leading cause of blindness. The accurate and …
DFCAFNet: Dual-feature co-attentive fusion network for diabetic retinopathy grading
Diabetic retinopathy (DR) grading is a complicated task characterized by inter-class
variations among several categories, the subtle detection of tiny lesions, and uneven data …
variations among several categories, the subtle detection of tiny lesions, and uneven data …
Diabetic retinopathy detection using a well-calibrated uncertainty aware convolutional neural network
The early detection of diabetic retinopathy is crucial in preventing irreversible vision loss,
making it a critical concern in healthcare. While deep learning models have shown …
making it a critical concern in healthcare. While deep learning models have shown …
Hybrid clustering strategies for effective oversampling and undersampling in multiclass classification
Multiclass imbalance is a challenging problem in real-world datasets, where certain classes
may have a low number of samples because they correspond to rare occurrences. To …
may have a low number of samples because they correspond to rare occurrences. To …
Identifying Diabetic Retinopathy in the Human Eye: A Hybrid Approach Based on a Computer-Aided Diagnosis System Combined with Deep Learning
Diagnosing and screening for diabetic retinopathy is a well-known issue in the biomedical
field. A component of computer-aided diagnosis that has advanced significantly over the …
field. A component of computer-aided diagnosis that has advanced significantly over the …