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Continuous sleep depth profiling from a single ECG lead reveals distinct sleep phenotypes and predicts mortality, outperforming traditional sleep staging.
EchoBridge boosts classification performance by nearly 8 points in AUROC, especially for rare cardiac conditions that are often overlooked.
Completing incomplete ECGs can restore diagnostic performance to near-complete levels, unlocking the potential of vast clinical archives for AI applications.
CausalMoE not only sets a new benchmark for Granger causal discovery but also excels in few-shot learning, revealing the power of heterogeneous expert routing in complex temporal analyses.
Unlock scalable cardio-sleep insights by repurposing ubiquitous single-lead ECG data for accurate sleep phenotyping, rivalling resource-intensive polysomnography.