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Echocardiography

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Machine Learning of Cardiac Anatomy and the Risk of New-Onset Atrial Fibrillation After TAVR.

JACC. Clinical electrophysiology
BACKGROUND: New-onset atrial fibrillation (NOAF) occurs in 5% to 15% of patients who undergo transfemoral transcatheter aortic valve replacement (TAVR). Cardiac imaging has been underutilized to predict NOAF following TAVR.

Automatic Segmentation for Analysis of Murine Cardiac Ultrasound and Photoacoustic Image Data Using Deep Learning.

Ultrasound in medicine & biology
OBJECTIVE: Although there are methods to identify regions of interest (ROIs) from echocardiographic images of myocardial tissue, they are often time-consuming and difficult to create when image quality is poor. Further, while myocardial strain from u...

Investigation on ultrasound images for detection of fetal congenital heart defects.

Biomedical physics & engineering express
Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but is hampered by the relatively low detection rates (i.e., 60%) of current screening technology. The d...

Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases.

Aging
BACKGROUND: Valvular heart disease (VHD) is becoming increasingly important to manage the risk of future complications. Electrocardiographic (ECG) changes may be related to multiple VHDs, and (AI)-enabled ECG has been able to detect some VHDs. We aim...

Artificial Intelligence Assessment of Biological Age From Transthoracic Echocardiography: Discrepancies with Chronologic Age Predict Significant Excess Mortality.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Age and sex can be estimated using artificial intelligence on the basis of various sources. The aims of this study were to test whether convolutional neural networks could be trained to estimate age and predict sex using standard transtho...

Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Pediatric cardiology
Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disease. Quantitative assessment of PR fraction (PRF) by echocardiography is limited. Cardiac MRI (cMRI) is the reference-standard for PRF quantification. ...

A novel multi-task machine learning classifier for rare disease patterning using cardiac strain imaging data.

Scientific reports
To provide accurate predictions, current machine learning-based solutions require large, manually labeled training datasets. We implement persistent homology (PH), a topological tool for studying the pattern of data, to analyze echocardiography-based...