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Between patterns and predictions: Interpretable latent EEG representations for clinical insights.

NeuroImage. Clinical · 2026-10-14

Laura Krumm, Robert Terziev, Dominik D Kranz et al.

Researchers applied a pretrained EEG embedding framework without retraining to three independent cohorts, including 575 cardiac arrest patients, 100 patients with subarachnoid hemorrhage, and 141 routine EEG recordings. EEG segments were mapped into a 128-dimensional space anchored by expert-derived reference brain states. Favorable outcomes or physiological recordings lay closer to healthy reference states, whereas poor outcomes and pathological recordings shifted toward pathological regions. Trajectory-derived geometric and temporal features discriminated outcomes after cardiac arrest with ROC-AUC 0.83 and after subarachnoid hemorrhage with ROC-AUC 0.76.

Clinical bottom line

This EEG representation showed potentially useful outcome discrimination after cardiac arrest. The abstract does not establish its incremental clinical value or suitability for individual prognostic decisions.

Study limitation: The abstract does not specify outcome definitions, assessment timing, or uncertainty around discrimination estimates.

Read the original on PubMed

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