Background: Cardiovascular disease, such as coronary heart disease (CHD), are the main
cause of mortality and morbidity worldwide. CHD is not entirely predicted by classic risk …

BACKGROUND Coronary heart disease (CHD) is among the main causes of death in the
world. Individual study of cardiovascular risk is an important way to predict CHD risk. The …

Adequate personalized numerical simulation of hemodynamic indices in coronary arteries
requires accurate identification of the key parameters. Elastic properties of coronary vessels …

Background: Non-invasive tests leading to elective coronary angiography (CAG) have low
diagnostic yield for obstructive coronary heart disease (CHD). Aortic stiffness, an …

BACKGROUND. Artificial neural networks (ANNs) are computer algorithms inspired by the
highly interactive processing of the human brain. When exposed to complex data sets, ANNs …

OBJECTIVE: In biomedical signal classification, due to the huge amount of data, to
compress the biomedical waveform data is vital. This paper presents two different structures …

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 …

Objective The main goal of this study was to develop an automatic method based on
supervised learning methods, able to distinguish healthy from pathologic arterial pulse wave …

Objective: Eight different learning algorithms used for creating artificial neural network (ANN)
models and the different ANN models in the prediction of coronary artery disease (CAD) are …

The diagnosis of heart diseases is a difficult task generally addressed by an appropriate
examination of patients' clinical data. Recently, the use of heart rate variability (HRV) …