AIMC Topic: Ventricular Dysfunction, Left
Clear Filters Showing 21 to 30 of 80 articles
Electrocardiogram-based deep learning model to screen peripartum cardiomyopathy.
American journal of obstetrics & gynecology MFM
Oct 30, 2023
BACKGROUND: Peripartum cardiomyopathy, one of the most fatal conditions during delivery, results in heart failure secondary to left ventricular systolic dysfunction. Left ventricular dysfunction can result in abnormalities in electrocardiography. How...
Deep learning-based prognostic model using non-enhanced cardiac cine MRI for outcome prediction in patients with heart failure.
European radiology
Jun 7, 2023
OBJECTIVES: To evaluate the performance of a deep learning-based multi-source model for survival prediction and risk stratification in patients with heart failure.
Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Mar 16, 2023
AIMS: Assessment of left ventricular (LV) function by echocardiography is hampered by modest test-retest reproducibility. A novel artificial intelligence (AI) method based on deep learning provides fully automated measurements of LV global longitudin...
Video-Based Deep Learning for Automated Assessment of Left Ventricular Ejection Fraction in Pediatric Patients.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Feb 7, 2023
BACKGROUND: Significant interobserver and interstudy variability occurs for left ventricular (LV) functional indices despite standardization of measurement techniques. Artificial intelligence models trained on adult echocardiograms are not likely to ...
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...
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 Detection of Left Ventricular Systolic Dysfunction Using Chest X-Rays: Prospective Validation, Please.
The Canadian journal of cardiology
Feb 15, 2022
Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort.
PLoS neglected tropical diseases
Dec 6, 2021
BACKGROUND: Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm sh...
Pushing the Limits of the ECG: Can We Assess Biventricular Function Without Imaging?
JACC. Cardiovascular imaging
Oct 13, 2021
Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram.
JACC. Cardiovascular imaging
Oct 13, 2021
OBJECTIVES: This study sought to develop DL models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population.
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