Deep Learning-based prediction of Diabetic Retinopathy using CLAHE and ESRGAN for Enhancement
Vision loss can be avoided if diabetic retinopathy (DR) is diagnosed and treated promptly.
The main five DR stages are none, moderate, mild, proliferate, and severe. In this study, a …
The main five DR stages are none, moderate, mild, proliferate, and severe. In this study, a …
A review of convolutional neural network based methods for medical image classification
C Chen, NAM Isa, X Liu - Computers in Biology and Medicine, 2025 - Elsevier
This study systematically reviews CNN-based medical image classification methods. We
surveyed 149 of the latest and most important papers published to date and conducted an in …
surveyed 149 of the latest and most important papers published to date and conducted an in …
Yolo-based deep learning model for pressure ulcer detection and classification
Pressure ulcers are significant healthcare concerns affecting millions of people worldwide,
particularly those with limited mobility. Early detection and classification of pressure ulcers …
particularly those with limited mobility. Early detection and classification of pressure ulcers …
A systematic review of real-time deep learning methods for image-based cancer diagnostics
H Sriraman, S Badarudeen, S Vats… - Journal of …, 2024 - Taylor & Francis
Deep Learning (DL) drives academics to create models for cancer diagnosis using medical
image processing because of its innate ability to recognize difficult-to-detect patterns in …
image processing because of its innate ability to recognize difficult-to-detect patterns in …
[PDF][PDF] Automated Knowledge Transfer for Medical Image Segmentation Using Deep Learning
J Mistry - Journal of Xidian University, 2024 - researchgate.net
The usage of deep trends for scientific photograph segmentation has seen a speedy
increase in recognition in recent years of today's capability to generate accurate photo …
increase in recognition in recent years of today's capability to generate accurate photo …
A federated learning approach to breast cancer prediction in a collaborative learning framework
Breast cancer continues to pose a substantial worldwide public health concern,
necessitating the use of sophisticated diagnostic methods to enable timely identification and …
necessitating the use of sophisticated diagnostic methods to enable timely identification and …
Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer
Breast cancer, a prevalent cancer among women worldwide, necessitates precise and
prompt detection for successful treatment. While conventional histopathological examination …
prompt detection for successful treatment. While conventional histopathological examination …
Deep learning-based ensemble model for classification of breast cancer
Deep learning (DL)-based categorization and detection methods for breast cancer diagnosis
through medical images are utilized by computer-aided diagnosis (CAD) techniques. In this …
through medical images are utilized by computer-aided diagnosis (CAD) techniques. In this …
Automated brain tumor segmentation and classification in MRI using YOLO-based Deep Learning
Recent advancements in image processing and computer vision have brought significant
transformations in healthcare technology, leading to significant improvements in diagnosis …
transformations in healthcare technology, leading to significant improvements in diagnosis …
Detection of breast cancer by deep belief network with improved activation function
S Archana - International Journal of Adaptive Control and …, 2024 - Wiley Online Library
Breast cancer is the most prevalent kind of tumor to occur in females and the primary cause
of death for women. Early detection is perhaps the most successful strategy to minimize …
of death for women. Early detection is perhaps the most successful strategy to minimize …