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ICU-EEG Pattern Detection by a Convolutional Neural Network
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DOI：10.1002/acn3.70164.png)
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Abstract
En 中文
Patients in the intensive care unit (ICU) often require continuous EEG (cEEG) monitoring due to the high risk of seizures and rhythmic and periodic patterns (RPPs). However, interpreting cEEG in real time is resource-intensive and heavily relies on specialized expertise, which is not always available. This study introduces a lightweight convolutional neural network (CNN) to automatically detect key EEG patterns, including seizures and RPPs.
Keywords:
deep learning
electroencephalography
intensive care units
seizures
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