AIMC Topic: Ventricular Function, Left

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Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients With Ischemic Cardiomyopathy.

Circulation. Arrhythmia and electrophysiology Mar 18, 2020
BACKGROUND: Transition zones between healthy myocardium and scar form a spatially complex substrate that may give rise to reentrant ventricular arrhythmias (VAs). We sought to assess the utility of a novel machine learning approach for quantifying 3-...
Diagnosis, Computer-Assisted Imaging, Three-Dimensional United States Contrast Media Magnetic Resonance Imaging Ventricular Function, Left Stroke Volume Middle Aged Risk Assessment Myocardial Ischemia Cardiomyopathies Fourier Analysis Gadolinium DTPA Retrospective Studies Death, Sudden, Cardiac Female Humans Action Potentials Risk Factors Aged Machine Learning Predictive Value of Tests Male Prognosis Registries Arrhythmias, Cardiac Heart Rate
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Deep Learning for Assessment of Left Ventricular Ejection Fraction from Echocardiographic Images.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Feb 25, 2020
Echocardiography Deep Learning Ventricular Dysfunction, Left Humans Ventricular Function, Left Stroke Volume
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Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.

Biomedical physics & engineering express Feb 18, 2020
BACKGROUND: Magnetic resonance cine imaging is the accepted standard for cardiac functional assessment. Left ventricular (LV) segmentation plays a key role in volumetric functional quantification of the heart. Conventional manual analysis is time-con...
Deep Learning Image Processing, Computer-Assisted Heart Ventricles Heart Diseases Observer Variation Humans Neural Networks, Computer Algorithms Ventricular Function, Left Automation Magnetic Resonance Imaging, Cine
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Assessing and Mitigating Bias in Medical Artificial Intelligence: The Effects of Race and Ethnicity on a Deep Learning Model for ECG Analysis.

Circulation. Arrhythmia and electrophysiology Feb 16, 2020
BACKGROUND: Deep learning algorithms derived in homogeneous populations may be poorly generalizable and have the potential to reflect, perpetuate, and even exacerbate racial/ethnic disparities in health and health care. In this study, we aimed to (1)...
Humans Artificial Intelligence Retrospective Studies Middle Aged Ethnicity Deep Learning Racial Groups Female Electrocardiography Follow-Up Studies Male Heart Ventricles Ventricular Function, Left
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Enhanced Diagnosis of Severe Aortic Stenosis Using Artificial Intelligence: A Proof-of-Concept Study of 530,871 Echocardiograms.

JACC. Cardiovascular imaging Dec 18, 2019
Humans Echocardiography Middle Aged Severity of Illness Index Hemodynamics Artificial Intelligence Diagnosis, Computer-Assisted Aged Aortic Valve Stenosis Databases, Factual Aged, 80 and over Aortic Valve Prognosis Adult Predictive Value of Tests Female Male Image Interpretation, Computer-Assisted Ventricular Function, Left Proof of Concept Study
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Machine learning based quantification of ejection and filling parameters by fully automated dynamic measurement of left ventricular volumes from cardiac magnetic resonance images.

Magnetic resonance imaging Dec 12, 2019
BACKGROUND: Although analysis of cardiac magnetic resonance (CMR) images provides accurate and reproducible measurements of left ventricular (LV) volumes, these measurements are usually not performed throughout the cardiac cycle because of lack of to...
Male Magnetic Resonance Imaging Ventricular Function, Left Prospective Studies Humans Heart Middle Aged Female Heart Ventricles Machine Learning Image Processing, Computer-Assisted Reproducibility of Results Automation Software Aged Endocardium Algorithms Adult
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A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type.

Scandinavian cardiovascular journal : SCJ Oct 18, 2019
In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischaemic cardiomyopathy. We aim to examine the predictive value of echocardiographic strain features alone and in combination with other features to differ...
Stroke Volume Echocardiography Middle Aged Diagnosis, Computer-Assisted Diagnosis, Differential Predictive Value of Tests Heart Failure Image Interpretation, Computer-Assisted Female Cardiomyopathies Reproducibility of Results Humans Aged Neural Networks, Computer Male Ventricular Function, Left Prognosis Retrospective Studies
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Combining Artificial Intelligence With Human Insight to Automate Echocardiography.

Circulation. Cardiovascular imaging Sep 16, 2019
Ventricular Function, Left Stroke Volume Echocardiography Humans Artificial Intelligence Machine Learning Algorithms
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Automated Echocardiographic Quantification of Left Ventricular Ejection Fraction Without Volume Measurements Using a Machine Learning Algorithm Mimicking a Human Expert.

Circulation. Cardiovascular imaging Sep 16, 2019
BACKGROUND: Echocardiographic quantification of left ventricular (LV) ejection fraction (EF) relies on either manual or automated identification of endocardial boundaries followed by model-based calculation of end-systolic and end-diastolic LV volume...
Humans Machine Learning Male Ventricular Function, Left Retrospective Studies Stroke Volume Female Echocardiography Reproducibility of Results Automation Aged Sensitivity and Specificity
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Fully Automated, Quality-Controlled Cardiac Analysis From CMR: Validation and Large-Scale Application to Characterize Cardiac Function.

JACC. Cardiovascular imaging Jul 17, 2019
OBJECTIVES: This study sought to develop a fully automated framework for cardiac function analysis from cardiac magnetic resonance (CMR), including comprehensive quality control (QC) algorithms to detect erroneous output.
Deep Learning Predictive Value of Tests Quality Control Heart Diseases Male Humans Image Interpretation, Computer-Assisted Ventricular Function, Left Female Quality Indicators, Health Care Stroke Volume Reproducibility of Results Automation Middle Aged Aged Magnetic Resonance Imaging, Cine Diagnosis, Computer-Assisted Ventricular Function, Right
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