#waveform-analysis News & Analysis

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

2 articles

AIBullisharXiv – CS AI · May 127/10

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Event Fields: Learning Latent Event Structure for Waveform Foundation Models

Researchers introduce a novel waveform foundation model that represents physiological signals as latent event processes rather than sequential tokens, using self-supervised learning to capture clinically meaningful structure. The approach demonstrates improved performance on medical benchmarks including arrhythmia classification and hemodynamic prediction, suggesting event-centric representations may be more suitable for healthcare AI than traditional sequence-based methods.

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.