Stages-based ECG signal analysis from traditional signal processing to machine learning approaches: A survey
Electrocardiogram (ECG) gives essential information about different cardiac conditions of
the human heart. Its analysis has been the main objective among the research community to …
the human heart. Its analysis has been the main objective among the research community to …
Arterial stiffness in hypertension and function of large arteries
BACKGROUND Arterial stiffness—typically assessed from non-invasive measurement of
pulse wave velocity along a straight portion of the vascular tree between the right common …
pulse wave velocity along a straight portion of the vascular tree between the right common …
Application of cross wavelet transform for ECG pattern analysis and classification
In this paper, we use cross wavelet transform (XWT) for the analysis and classification of
electrocardiogram (ECG) signals. The cross-correlation between two time-domain signals …
electrocardiogram (ECG) signals. The cross-correlation between two time-domain signals …
Machine learning strategy for gut microbiome-based diagnostic screening of cardiovascular disease
Cardiovascular disease (CVD) is the number one leading cause for human mortality.
Besides genetics and environmental factors, in recent years, gut microbiota has emerged as …
Besides genetics and environmental factors, in recent years, gut microbiota has emerged as …
Inferior myocardial infarction detection using stationary wavelet transform and machine learning approach
Early and accurate detection of myocardial infarction is imperative for reducing the mortality
rate due to heart attack. Present work proposes a novel technique aiming toward accurate …
rate due to heart attack. Present work proposes a novel technique aiming toward accurate …
A review of automated methods for detection of myocardial ischemia and infarction using electrocardiogram and electronic health records
There is a growing body of research focusing on automatic detection of ischemia and
myocardial infarction (MI) using computer algorithms. In clinical settings, ischemia and MI …
myocardial infarction (MI) using computer algorithms. In clinical settings, ischemia and MI …
[HTML][HTML] Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters
OY Atkov, SG Gorokhova, AG Sboev, EV Generozov… - Journal of …, 2012 - Elsevier
The aim of this study was to develop an artificial neural networks-based (ANNs) diagnostic
model for coronary heart disease (CHD) using a complex of traditional and genetic factors of …
model for coronary heart disease (CHD) using a complex of traditional and genetic factors of …
A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree
OBJECTIVE: In the current work we propose a methodology for the automated creation of
fuzzy expert systems, applied in ischaemic and arrhythmic beat classification. METHODS …
fuzzy expert systems, applied in ischaemic and arrhythmic beat classification. METHODS …
Multiclass ECG signal analysis using global average-based 2-D convolutional neural network modeling
Cardiovascular diseases have been reported to be the leading cause of mortality across the
globe. Among such diseases, Myocardial Infarction (MI), also known as “heart attack”, is of …
globe. Among such diseases, Myocardial Infarction (MI), also known as “heart attack”, is of …
[PDF][PDF] Designing an artificial neural network model for the prediction of thrombo-embolic stroke
D Shanthi, G Sahoo, N Saravanan - International Journals of Biometric and …, 2009 - Citeseer
In this study, a functional model of ANN is proposed to aid existing diagnosis methods. This
work investigated the use of Artificial Neural Networks (ANN) in predicting the Thrombo …
work investigated the use of Artificial Neural Networks (ANN) in predicting the Thrombo …