Artificial Intelligence #eeg#foundation models
EEG Foundation Models Show Promise for Burst-Suppression Detection in ICU Without Patient-Specific Calibration
A new study on arXiv evaluates three EEG foundation models—REVE-base, LUNA-large, and LuMamba-Tiny—for automatic burst-suppression detection in ICU patients, finding REVE-base achieves the highest event-based F1-score (0.868) and reduces burst-per-minute error by 52.1% compared to a task-specific EEGNet baseline.
Jul 8, 2026 1 source