matlab-deep-learning/Abnormal-EEG-Signal-Classification-Using-CNNs
This example shows how to build and train a convolutional neural network (CNN) from scratch to perform a classification task with an EEG dataset.
This helps neurologists and researchers automatically identify abnormal patterns in EEG brainwave recordings. It takes raw EEG signal data, like those from the Temple University Hospital corpus, and classifies them as either 'normal' or 'abnormal'. Clinical researchers and medical professionals who work with brain activity data would find this useful for screening or initial analysis.
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Use this if you need to quickly and consistently classify large volumes of EEG data to identify potential abnormalities without manual review.
Not ideal if you need to analyze highly specialized or rare EEG anomalies, or if you don't have access to MATLAB and its Deep Learning Toolbox.
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Jan 09, 2023
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