A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
[HTML][HTML] A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram
The success of deep learning over the traditional machine learning techniques in handling
artificial intelligence application tasks such as image processing, computer vision, object …
artificial intelligence application tasks such as image processing, computer vision, object …
Generalization of Dempster–Shafer theory: A complex mass function
F Xiao - Applied Intelligence, 2020 - Springer
Dempster–Shafer evidence theory has been widely used in various fields of applications,
because of the flexibility and effectiveness in modeling uncertainties without prior …
because of the flexibility and effectiveness in modeling uncertainties without prior …
Combining time-series evidence: A complex network model based on a visibility graph and belief entropy
X Song, F Xiao - Applied Intelligence, 2022 - Springer
Combining basic probability assignments (BPAs) with time series is common in real-life
cases. Therefore, a new evidence fusion approach based on belief entropy and a visibility …
cases. Therefore, a new evidence fusion approach based on belief entropy and a visibility …
Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals
Electrocardiography (ECG) is widely used for arrhythmia detection nowadays. The machine
learning methods with signal processing algorithms have been used for automated …
learning methods with signal processing algorithms have been used for automated …
Optimized levy flight model for heart disease prediction using CNN framework in big data application
Cardiac disease is one of the most complex diseases globally. It affects the lives of humans
critically. It is essential for accurate and timely diagnosis to treat heart failure and prevent the …
critically. It is essential for accurate and timely diagnosis to treat heart failure and prevent the …
Interval-valued intuitionistic fuzzy Jenson-Shannon divergence and its application in multi-attribute decision making
Z Wang, F Xiao, W Ding - Applied Intelligence, 2022 - Springer
Abstract Interval-Valued Intuitionistic Fuzzy Set (IVIFS) is an effective tool to model
uncertainty, and has received much attention. When applying IVIFS to solve real problems …
uncertainty, and has received much attention. When applying IVIFS to solve real problems …
Multi-domain modeling of atrial fibrillation detection with twin attentional convolutional long short-term memory neural networks
Atrial fibrillation (AF) is a common arrhythmia, and its incidence increases with age. Many
methods have been developed to identify AF, including both the hand-picked features by …
methods have been developed to identify AF, including both the hand-picked features by …
Automatic seizure detection by convolutional neural networks with computational complexity analysis
Abstract Background and Objectives Nowadays, an automated computer-aided diagnosis
(CAD) is an approach that plays an important role in the detection of health issues. The main …
(CAD) is an approach that plays an important role in the detection of health issues. The main …
Automated heartbeat classification based on deep neural network with multiple input layers
H Shi, C Qin, D Xiao, L Zhao, C Liu - Knowledge-Based Systems, 2020 - Elsevier
The arrhythmia is an important group of cardiovascular disease. Electrocardiogram (ECG) is
commonly used for detecting arrhythmias. Computer-aided diagnosis system can diagnose …
commonly used for detecting arrhythmias. Computer-aided diagnosis system can diagnose …