BrainNet: optimal deep learning feature fusion for brain tumor classification
Early detection of brain tumors can save precious human life. This work presents a fully
automated design to classify brain tumors. The proposed scheme employs optimal deep …
automated design to classify brain tumors. The proposed scheme employs optimal deep …
LCDAE: data augmented ensemble framework for lung cancer classification
Objective: The only possible solution to increase the patients' fatality rate is lung cancer
early-stage detection. Recently, deep learning techniques became the most promising …
early-stage detection. Recently, deep learning techniques became the most promising …
[HTML][HTML] GestroNet: A framework of saliency estimation and optimal deep learning features based gastrointestinal diseases detection and classification
In the last few years, artificial intelligence has shown a lot of promise in the medical domain
for the diagnosis and classification of human infections. Several computerized techniques …
for the diagnosis and classification of human infections. Several computerized techniques …
NVAS: a non-interactive verifiable federated learning aggregation scheme for COVID-19 based on game theory
H Deng, J Hu, R Sharma, M Mo, Y Ren - Computer communications, 2023 - Elsevier
The continued spread of COVID-19 seriously endangers the physical and mental health of
people in all countries. It is an important method to establish inter agency COVID-19 …
people in all countries. It is an important method to establish inter agency COVID-19 …
[PDF][PDF] A healthcare system for COVID19 classification using multi-type classical features selection
The coronavirus (COVID19), also known as the novel coronavirus, first appeared in
December 2019 in Wuhan, China. After that, it quickly spread throughout the world and …
December 2019 in Wuhan, China. After that, it quickly spread throughout the world and …
[HTML][HTML] Automated identification of human gastrointestinal tract abnormalities based on deep convolutional neural network with endoscopic images
As a powerful analytic tool for medical image analysis, particularly for endoscopic image
interpretation, deep convolutional neural network (DCNN) has gained remarkable attention …
interpretation, deep convolutional neural network (DCNN) has gained remarkable attention …
Hybrid techniques for diagnosing endoscopy images for early detection of gastrointestinal disease based on fusion features
Z Ghaleb Al-Mekhlafi… - … Journal of Intelligent …, 2023 - Wiley Online Library
Gastrointestinal (GI) diseases, particularly tumours, are considered one of the most
widespread and dangerous diseases and thus need timely health care for early detection to …
widespread and dangerous diseases and thus need timely health care for early detection to …
[HTML][HTML] A Comparative Analysis of Optimization Algorithms for Gastrointestinal Abnormalities Recognition and Classification Based on Ensemble XcepNet23 and …
Esophagitis, cancerous growths, bleeding, and ulcers are typical symptoms of
gastrointestinal disorders, which account for a significant portion of human mortality. For …
gastrointestinal disorders, which account for a significant portion of human mortality. For …
GastroNet: A robust attention‐based deep learning and cosine similarity feature selection framework for gastrointestinal disease classification from endoscopic images
Diseases of the Gastrointestinal (GI) tract significantly affect the quality of human life and
have a high fatality rate. Accurate diagnosis of GI diseases plays a pivotal role in healthcare …
have a high fatality rate. Accurate diagnosis of GI diseases plays a pivotal role in healthcare …
[HTML][HTML] A new approach for gastrointestinal tract findings detection and classification: Deep learning-based hybrid stacking ensemble models
Endoscopic procedures for diagnosing gastrointestinal tract findings depend on specialist
experience and inter-observer variability. This variability can cause minor lesions to be …
experience and inter-observer variability. This variability can cause minor lesions to be …