LVEF Prediction During ACS Using AI Algorithm Applied on Coronary Angiogram Videos
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New AI model Echo-E3Net efficiently estimates cardiac ejection fraction
Researchers have developed Echo-E$^3$Net, a novel deep learning model designed for efficient estimation of left ventricular ejection fraction (LVEF) from cardiac imaging. This network explicitly incorporates cardiac ana…
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DINOv2 framework unifies cardiac assessment tasks, improves LVEF estimation
Researchers have developed a unified framework using the DINOv2 foundation model to address three distinct cardiac assessment tasks: Left Ventricular Ejection Fraction (LVEF) estimation, global longitudinal strain (GLS)…
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Vision Transformer Detects Heart Condition from ECGs with High Accuracy
Researchers have developed a vision transformer model capable of detecting reduced left ventricular ejection fraction (LVEF) from standard electrocardiograms (ECGs). The model, trained on over 10,000 patients across mul…
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Foundation models adapted for cardiac MRI analysis achieve strong segmentation and ejection fraction estimation
Researchers have adapted foundation models for analyzing cardiac MRI scans, achieving strong results in segmenting different views of cine MRI and estimating ejection fraction. The models demonstrated high Dice scores f…
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Deep learning model predicts sudden cardiac death using ECG biomarkers
Researchers have developed a deep learning model capable of identifying electrocardiogram (ECG) biomarkers that predict sudden cardiac death. This AI-driven approach demonstrates superior performance compared to traditi…