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Arrhythmic Sudden Death Survival Prediction using Deep Learning Analysis of Scarring in the Heart

Unmet Need:Sudden cardiac death (SCD) is a leading cause of death in western countries, accounting for 15 – 20% of deaths (Kumar, et al. 2021). Currently, the standard for estimating risk for SCD is based on a left ventricular ejection fraction (LVEF) lower than 30-35% (Russo et al, 2013) which captures only 20% of arrhythmic sudden cardiac deaths (SCDA)...

Published: 6/28/2024 | Inventor(s): Natalia Trayanova, Dan Popescu, Mauro Maggioni, Julie Shade

Keywords(s):

Category(s): Clinical and Disease Specializations > Cardiovascular, Clinical and Disease Specializations > Cardiovascular > Arrhythmia, Clinical and Disease Specializations > Cardiovascular > Arrhythmias, Clinical and Disease Specializations > Cardiovascular > Cardiac Arrest, Clinical and Disease Specializations > Cardiovascular > Ventricular Tachycardia, Clinical and Disease Specializations > Cardiovascular > Ventricular Fibrillation, Technology Classifications > Computers, Electronics & Software > Algorithms, Technology Classifications > Computers, Electronics & Software > Artificial Intelligence, Technology Classifications > Computers, Electronics & Software > Image Processing & Analysis, Technology Classifications > Computers, Electronics & Software > Machine Learning

Anatomically-Informed Deep Learning on Contrast-Enhanced Cardiac MRI for Scar Segmentation and Clinical Feature Extraction

Unmet NeedHeart disease is the leading cause of death worldwide with 30.3 million Americans diagnosed with heart disease in 2018, according to the CDC. The leading diagnostic method is to identify myocardial fibrosis (scarring), which is a leading indicator of sudden cardiac death (SCD). Current image segmentation involves cardiac magnetic resonance...

Published: 6/28/2024 | Inventor(s): Natalia Trayanova, Haley Abramson, Dan Popescu, Mauro Maggioni, Katherine Wu

Keywords(s):

Category(s): Clinical and Disease Specializations > Cardiovascular, Technology Classifications > Diagnostics > Diagnostic Imaging, Technology Classifications > Computers, Electronics & Software > Artificial Intelligence