AIMC Topic: Models, Cardiovascular

Clear Filters Showing 121 to 130 of 164 articles

Machine Learning Approach for Predicting Wall Shear Distribution for Abdominal Aortic Aneurysm and Carotid Bifurcation Models.

IEEE journal of biomedical and health informatics
Computer simulations based on the finite element method represent powerful tools for modeling blood flow through arteries. However, due to its computational complexity, this approach may be inappropriate when results are needed quickly. In order to r...

Noninvasive Personalization of a Cardiac Electrophysiology Model From Body Surface Potential Mapping.

IEEE transactions on bio-medical engineering
GOAL: We use noninvasive data (body surface potential mapping, BSPM) to personalize the main parameters of a cardiac electrophysiological (EP) model for predicting the response to different pacing conditions.

Predicting the physiological response of Tivela stultorum hearts with digoxin from cardiac parameters using artificial neural networks.

Bio Systems
Multi-layer perceptron artificial neural networks (MLP-ANNs) were used to predict the concentration of digoxin needed to obtain a cardio-activity of specific biophysical parameters in Tivela stultorum hearts. The inputs of the neural networks were th...

Prediction of blood-brain barrier permeability of organic compounds.

Doklady. Biochemistry and biophysics
Using fragmental descriptors and artificial neural networks, a predictive model of the relationship between the structure of organic compounds and their blood-brain barrier permeability was constructed and the structural factors affecting the readine...

Developing new VOmax prediction models from maximal, submaximal and questionnaire variables using support vector machines combined with feature selection.

Computers in biology and medicine
Maximal oxygen uptake (VOmax) is an essential part of health and physical fitness, and refers to the highest rate of oxygen consumption an individual can attain during exhaustive exercise. In this study, for the first time in the literature, we combi...

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.

IEEE transactions on bio-medical engineering
GOAL: In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained fully connected conditional random field model.

Symbolic features and classification via support vector machine for predicting death in patients with Chagas disease.

Computers in biology and medicine
This paper introduces a technique for predicting death in patients with Chagas disease using features extracted from symbolic series and time-frequency indices of heart rate variability (HRV). The study included 150 patients: 15 patients who died and...

Bayesian network modeling: A case study of an epidemiologic system analysis of cardiovascular risk.

Computer methods and programs in biomedicine
An extensive, in-depth study of cardiovascular risk factors (CVRF) seems to be of crucial importance in the research of cardiovascular disease (CVD) in order to prevent (or reduce) the chance of developing or dying from CVD. The main focus of data an...

Immediate hemodynamic changes after revascularization of complete infrarenal aortic occlusion: A classic issue revisited.

Medical hypotheses
Chronic total occlusion of the infrarenal aorta (CTOA) is a rare disease, characterized by severe impairment of limb perfusion. It is advocated that revascularization may improve survival rates, presumably due to improved cardiovascular performance; ...