Coronary heart disease diagnosis by artificial neural networks including aortic pulse wave velocity index and clinical parameters
A Vallée, A Cinaud, V Blachier, H Lelong… - Journal of …, 2019 - journals.lww.com
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 …
cause of mortality and morbidity worldwide. CHD is not entirely predicted by classic risk …
Added value of aortic pulse wave velocity index in a predictive diagnosis decision tree of coronary heart disease
A Vallée, L Petruescu, S Kretz, ME Safar… - American journal of …, 2019 - academic.oup.com
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 …
world. Individual study of cardiovascular risk is an important way to predict CHD risk. The …
Computational analysis of hemodynamic indices based on personalized identification of aortic pulse wave velocity by a neural network
T Gamilov, F Liang, P Kopylov, N Kuznetsova, A Rogov… - Mathematics, 2023 - mdpi.com
Adequate personalized numerical simulation of hemodynamic indices in coronary arteries
requires accurate identification of the key parameters. Elastic properties of coronary vessels …
requires accurate identification of the key parameters. Elastic properties of coronary vessels …
Added value of aortic pulse wave velocity index for the detection of coronary heart disease by elective coronary angiography
A Vallée, Y Zhang, A Protogerou, ME Safar… - Blood …, 2019 - Taylor & Francis
Background: Non-invasive tests leading to elective coronary angiography (CAG) have low
diagnostic yield for obstructive coronary heart disease (CHD). Aortic stiffness, an …
diagnostic yield for obstructive coronary heart disease (CHD). Aortic stiffness, an …
Recognition of patients with cardiovascular disease by artificial neural networks
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 …
highly interactive processing of the human brain. When exposed to complex data sets, ANNs …
Application of complex discrete wavelet transform in classification of Doppler signals using complex-valued artificial neural network
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 …
compress the biomedical waveform data is vital. This paper presents two different structures …
[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 …
Supervised learning methods for pathological arterial pulse wave differentiation: a SVM and neural networks approach
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 …
supervised learning methods, able to distinguish healthy from pathologic arterial pulse wave …
Predicting coronary artery disease using different artificial neural network models/Koroner arter hastaliginin degisik yapay sinir agi modelleri ile tahmini
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 …
models and the different ANN models in the prediction of coronary artery disease (CAD) are …
Identification of ischemic heart disease by using machine learning technique based on parameters measuring heart rate variability
G Silveri, M Merlo, L Restivo, B De Paola… - 2020 28th European …, 2021 - ieeexplore.ieee.org
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) …
examination of patients' clinical data. Recently, the use of heart rate variability (HRV) …