AIMC Topic: Models, Cardiovascular
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Localization of Ventricular Activation Origin from the 12-Lead ECG: A Comparison of Linear Regression with Non-Linear Methods of Machine Learning.
Annals of biomedical engineering
Nov 21, 2018
We have previously developed an automated localization method based on multiple linear regression (MLR) model to estimate the activation origin on a generic left-ventricular (LV) endocardial surface in real time from the 12-lead ECG. The present stud...
A unified non-linear approach based on recurrence quantification analysis and approximate entropy: application to the classification of heart rate variability of age-stratified subjects.
Medical & biological engineering & computing
Nov 3, 2018
This paper presents a unified approach based on the recurrence quantification analysis (RQA) and approximate entropy (ApEn) for the classification of heart rate variability (HRV). In this paper, the optimum tolerance threshold (r) corresponding to Ap...
Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.
Computers in biology and medicine
Oct 18, 2018
We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibrillation, are a major global healthcare challenge. Treatment is often th...
Transfer learning for classification of cardiovascular tissues in histological images.
Computer methods and programs in biomedicine
Aug 16, 2018
BACKGROUND AND OBJECTIVE: Automatic classification of healthy tissues and organs based on histology images is an open problem, mainly due to the lack of automated tools. Solutions in this regard have potential in educational medicine and medical prac...
Machine learning-aided exploration of relationship between strength and elastic properties in ascending thoracic aneurysm.
International journal for numerical methods in biomedical engineering
Apr 10, 2018
Machine learning was applied to classify tension-strain curves harvested from inflation tests on ascending thoracic aneurysm samples. The curves were classified into rupture and nonrupture groups using prerupture response features. Two groups of feat...
Model-Based Feature Augmentation for Cardiac Ablation Target Learning From Images.
IEEE transactions on bio-medical engineering
Mar 22, 2018
GOAL: We present a model-based feature augmentation scheme to improve the performance of a learning algorithm for the detection of cardiac radio-frequency ablation (RFA) targets with respect to learning from images alone.
Viscosity Prediction in a Physiologically Controlled Ventricular Assist Device.
IEEE transactions on bio-medical engineering
Jan 24, 2018
OBJECTIVE: We present a novel machine learning model to accurately predict the blood-analog viscosity during support of a pathological circulation with a rotary ventricular assist device (VAD). The aim is the continuous monitoring of the hematocrit (...
Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform.
Scientific reports
Jan 17, 2018
In this article, we offer an artificial intelligence method to estimate the carotid-femoral Pulse Wave Velocity (PWV) non-invasively from one uncalibrated carotid waveform measured by tonometry and few routine clinical variables. Since the signal pro...
Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks.
BMC bioinformatics
Dec 28, 2017
BACKGROUND: Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrh...
Modeling the control of the central nervous system over the cardiovascular system using support vector machines.
Computers in biology and medicine
Dec 15, 2017
The control of the central nervous system (CNS) over the cardiovascular system (CS) has been modeled using different techniques, such as fuzzy inductive reasoning, genetic fuzzy systems, neural networks, and nonlinear autoregressive techniques; the r...
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