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. Author manuscript; available in PMC: 2021 Nov 1.
Published in final edited form as: Stroke. 2020 Sep 18;51(11):3361–3365. doi: 10.1161/STROKEAHA.120.030150

Figure 1.

Figure 1.

[A]. The Quick-20 dry-lead Cognionics headset and the EEG montage, having 17 leads and 27 bipolar lead-pairs (blue lines). [B]. EEG from a 69 year-old male 8.5 hours after stroke onset with right thalamocapsular infarct and NIHSS=9. [C] ROC curves for each model. The model combining clinical and EEG data using deep learning showed best diagnostic performance for both acute stroke/TIA (left; AUC=87.8) and for acute stroke with LVO (right; AUC=86.4).