UncertaintyFuseNet: robust uncertainty-aware hierarchical feature fusion model with ensemble Monte Carlo dropout for COVID-19 detection
Abstract The COVID-19 (Coronavirus disease 2019) pandemic has become a major global
threat to human health and well-being. Thus, the development of computer-aided detection …
threat to human health and well-being. Thus, the development of computer-aided detection …
A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques
Nowadays, the development of new computer-based technologies has led to rapid increase
in the volume of user-generated textual content on the website. Patient-written medical and …
in the volume of user-generated textual content on the website. Patient-written medical and …
[HTML][HTML] Comparison of various approaches to combine logistic regression with genetic algorithms in survival prediction of hepatocellular carcinoma
Hepatocellular carcinoma (HCC) is the most common liver cancer in adults. Many different
factors make it difficult to diagnose in humans.. In this paper, a novel diagnostics approach …
factors make it difficult to diagnose in humans.. In this paper, a novel diagnostics approach …
Automated arrhythmia detection with homeomorphically irreducible tree technique using more than 10,000 individual subject ECG records
Background and objective Arrhythmia constitute a common clinical problem in cardiology.
The diagnosis is often made using electrocardiographic (ECG) signals but manual ECG …
The diagnosis is often made using electrocardiographic (ECG) signals but manual ECG …
[HTML][HTML] DUNEScan: a web server for uncertainty estimation in skin cancer detection with deep neural networks
B Mazoure, A Mazoure, J Bédard, V Makarenkov - Scientific Reports, 2022 - nature.com
Recent years have seen a steep rise in the number of skin cancer detection applications.
While modern advances in deep learning made possible reaching new heights in terms of …
While modern advances in deep learning made possible reaching new heights in terms of …
Automated Parkinson's disease recognition based on statistical pooling method using acoustic features
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous
system and hinders people's vital activities. The majority of Parkinson's patients lose their …
system and hinders people's vital activities. The majority of Parkinson's patients lose their …
A dynamic center and multi threshold point based stable feature extraction network for driver fatigue detection utilizing EEG signals
Driver fatigue is the one of the main reasons of the traffic accidents. The human brain is a
complex structure, whose function can be evaluated with electroencephalogram (EEG) …
complex structure, whose function can be evaluated with electroencephalogram (EEG) …
Feature selection based on improved binary global harmony search for data classification
Harmony search (HS) is an effective meta-heuristic algorithm inspired by the music
improvisation process, where musicians search for a pleasing harmony by adjusting their …
improvisation process, where musicians search for a pleasing harmony by adjusting their …
Evolutionary self-organizing fuzzy system using fuzzy-classification-based social learning particle swarm optimization
T Zhao, C Chen, H Cao - Information Sciences, 2022 - Elsevier
A self-organizing algorithm based on an online cluster and fuzzy sets update algorithm
(OCFU) and fuzzy-classification-based social learning particle swarm optimization (FC …
(OCFU) and fuzzy-classification-based social learning particle swarm optimization (FC …
A novel approach for coronary artery disease diagnosis using hybrid particle swarm optimization based emotional neural network
Coronary artery disease (CAD) can cause serious conditions such as severe heart attack,
heart failure, and angina in patients with cardiovascular problems. These conditions may be …
heart failure, and angina in patients with cardiovascular problems. These conditions may be …