#ecg News & Analysis

3 articles tagged with #ecg. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBullisharXiv – CS AI · Mar 46/103

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Detecting Structural Heart Disease from Electrocardiograms via a Generalized Additive Model of Interpretable Foundation-Model Predictors

Researchers developed an interpretable AI framework for detecting structural heart disease from electrocardiograms, achieving better performance than existing deep-learning methods while providing clinical transparency. The model demonstrated improvements of nearly 1% across key metrics using the EchoNext benchmark of over 80,000 ECG-ECHO pairs.

AINeutralarXiv – CS AI · Jun 196/10

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SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models

Researchers introduce SL-S4Wave, a self-supervised learning framework combining contrastive learning with structured state space models to analyze physiological waveforms like ECGs and EEGs. The approach outperforms existing methods in detecting arrhythmias, requires fewer labeled examples, and generalizes effectively across different cardiac conditions and brain signals.

AINeutralarXiv – CS AI · Feb 274/105

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Learning geometry-dependent lead-field operators for forward ECG modeling

Researchers developed a new AI-powered surrogate model for ECG simulations that combines geometry encoding with neural networks to predict lead-field gradients. The method achieves high accuracy (5° mean angular error, <2.5% relative error) while reducing computational costs and data requirements compared to traditional full-order models.