1: Using Artificial Intelligence to Rethink Seizure Management in the Neuro ICU
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1: Using Artificial Intelligence to Rethink Seizure Management in the Neuro ICU
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このコンテンツについて
In this initial episode, host Jennifer Frontera, MD, is joined by Sahar Zafar, MD, associate professor of neurology at Mass General Brigham and vice chair of quality, to discuss the expanding role of artificial intelligence (AI) in neurocritical care. The conversation explores how large-scale EEG data, electronic health records, and advanced causal modeling can be leveraged to address longstanding gaps in seizure management, prognostication, and trial design. In addition, Zafar outlines how AI-driven approaches are being used to annotate neurophysiologic data at scale, quantify seizure burden, and extract clinically meaningful outcomes from unstructured records. Together, they examine the challenges of model validation, generalizability across health systems, and how these tools may ultimately inform more precise, data-driven treatment strategies in the neuro ICU.
Episode Breakdown:
- 1:30 – Why evidence gaps and practice variation persist in neurocritical seizure management
- 4:50 – How AI and real-world data can address limitations of traditional clinical trials
- 8:10 – Using EEG-based AI models to quantify seizure burden and predict outcomes
- 10:40 – Applying NLP and large language models to extract meaningful data from EHRs
- 21:20 – Challenges of model validation, portability, and multicenter collaboration
- 26:20 – Future applications of AI for seizure prophylaxis, multimodal monitoring, and trial design
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