AIMC Topic: Ventricular Function, Left
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A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram.
Nature communications
Nov 9, 2022
This study compares a deep learning interpretation of 23 echocardiographic parameters-including cardiac volumes, ejection fraction, and Doppler measurements-with three repeated measurements by core lab sonographers. The primary outcome metric, the in...
Machine Learning-Enabled Fully Automated Assessment of Left Ventricular Volume, Ejection Fraction and Strain: Experience in Pediatric and Young Adult Echocardiography.
Pediatric cardiology
Oct 8, 2022
BACKGROUND: Left ventricular (LV) volumes, ejection fraction (EF), and myocardial strain have been shown to be predictive of clinical and subclinical heart disease. Automation of LV functional assessment overcomes difficult technical challenges and c...
Deep learning of ECG waveforms for diagnosis of heart failure with a reduced left ventricular ejection fraction.
Scientific reports
Aug 20, 2022
The performance and clinical implications of the deep learning aided algorithm using electrocardiogram of heart failure (HF) with reduced ejection fraction (DeepECG-HFrEF) were evaluated in patients with acute HF. The DeepECG-HFrEF algorithm was trai...
Revealing Unforeseen Diagnostic Image Features With Deep Learning by Detecting Cardiovascular Diseases From Apical 4-Chamber Ultrasounds.
Journal of the American Heart Association
Aug 5, 2022
Background With the increase of highly portable, wireless, and low-cost ultrasound devices and automatic ultrasound acquisition techniques, an automated interpretation method requiring only a limited set of views as input could make preliminary cardi...
A method using deep learning to discover new predictors from left-ventricular mechanical dyssynchrony for CRT response.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Aug 1, 2022
BACKGROUND: Studies have shown that the conventional parameters characterizing left ventricular mechanical dyssynchrony (LVMD) measured on gated SPECT myocardial perfusion imaging (MPI) have their own statistical limitations in predicting cardiac res...
Artificial intelligence (AI) versus expert: A comparison of left ventricular outflow tract velocity time integral (LVOT-VTI) assessment between ICU doctors and an AI tool.
Journal of applied clinical medical physics
Jul 11, 2022
PURPOSE: The application of point of care ultrasound (PoCUS) in medical education is a relatively new course. There are still great differences in the existence, quantity, provision, and depth of bedside ultrasound education. The left ventricular out...
Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy.
Science translational medicine
Jul 6, 2022
Dilated cardiomyopathy (DCM) is characterized by reduced cardiac output, as well as thinning and enlargement of left ventricular chambers. These characteristics eventually lead to heart failure. Current standards of care do not target the underlying ...
The Interfield Strength Agreement of Left Ventricular Strain Measurements at 1.5 T and 3 T Using Cardiac MRI Feature Tracking.
Journal of magnetic resonance imaging : JMRI
Jun 29, 2022
BACKGROUND: Left ventricular (LV) strain measurements can be derived using cardiac MRI from routinely acquired balanced steady-state free precession (bSSFP) cine images.
Performance of artificial intelligence for biventricular cardiovascular magnetic resonance volumetric analysis in the clinical setting.
The international journal of cardiovascular imaging
Jun 29, 2022
Cardiovascular magnetic resonance (CMR) derived ventricular volumes and function guide clinical decision-making for various cardiac pathologies. We aimed to evaluate the efficiency and clinical applicability of a commercially available artificial int...
Improving clinical trial efficiency using a machine learning-based risk score to enrich study populations.
European journal of heart failure
May 22, 2022
AIMS: Prognostic enrichment strategies can make trials more efficient, although potentially at the cost of diminishing external validity. Whether using a risk score to identify a population at increased mortality risk could improve trial efficiency i...
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