Fig. 2: Segment of EEG with seizure and comparison of different model outputs.
From: Scaling convolutional neural networks achieves expert level seizure detection in neonatal EEG
a Sixty second sample of EEG, from the development dataset, with per-channel seizure annotations shaded. In this example, only 3/8 channels contain seizure. b Annotation and model outputs for 10 h from C4-O2 of the same EEG recording. The EEG sample in (a) corresponds to the first 60 s of the first seizure event in (b). Models of different scales---namely the Nano, Small, Medium, Large, and Extra Large (XL) models---become more confident, suppressing the output for non-seizure periods while maintaining high agreement in seizure periods. This ease of interpretation would be beneficial to clinical implementation that use a real-time model output trace.
