Single-patient 50% discount cross-validation experiments for the CGTNet model based on the CHB-MIT dataset.

<p>Single-patient 50% discount cross-validation experiments for the CGTNet model based on the CHB-MIT dataset.</p>

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Bibliographic Details
Main Author:	Dianli Wang (22765892) (author)
Other Authors:	Enping Li (17301730) (author), Yang Wang (5921) (author), Zhiyang Liu (4332328) (author), Aixia Sun (5269634) (author), Wei Wei (21173) (author), Xuning Zhang (6934130) (author), Cheng Peng (118834) (author), Fengtao Wei (22765895) (author)
Published:	2025
Subjects:	Biochemistry Neuroscience Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified scale convolutional network predict epileptic seizures handling spatiotemporal features gated recurrent units extract spatiotemporal features effective new tool current models struggle causing significant burdens 89 %, sensitivity 52 %, specificity processing medical signals cgtnet incorporating spatio ethz eeg datasets 53 %, eeg signals technical innovations specifically designed sparse transformers seizure prediction rigorous evaluation research provides renowned chb paper introduces model achieved mcc value innovative approach immense potential grus ), exceptional performance early detection deep learning continuous monitoring computational efficiency cgtnet enhances auroc value analyzing elec also validate advancing healthcare
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