Frontlines with Frontera: Using Artificial Intelligence to Rethink Seizure Management in the Neuro ICU
This NeurologyLive “Frontlines with Frontera” episode digs into where AI/ML can actually help in the neuro ICU, where data is high-volume (continuous EEG) and decision-making is time-sensitive. Host Jennifer Frontera speaks with Sahar Zafar about how models could reduce the manual burden of EEG labeling, quantify seizure burden more consistently, and combine EEG + electronic health record data to support research and bedside decision support.
One of the most useful through-lines is the gap between promising retrospective results and real clinical deployment: generalizing across hospitals, differences in monitoring setups, and the need for careful validation (including prospective evaluation) before any model influences care. The episode also touches on newer directions like NLP/LLMs for extracting outcomes and context from clinical notes, and the importance of collaboration (shared datasets, common definitions, and reproducible evaluation) to avoid “one-center” models that don’t travel. If you want a quick entry point, scan the episode breakdown first, then jump to the segments on validation/generalizability and how they think about integrating these tools into ICU workflow.