AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
A neonatal seizure detection algorithm that uses a combination of aEEG and CSA clinical features can capture seizures in HIE patients and performance across seizure patients is not correlated with seizure duration.
These findings demonstrate that recent advances in ML and DL enable reliable prediction of preictal states using ECG alone and indicate that training models on long-term ECG recordings containing multiple seizures from the same individual yields a more dependable solution for seizure prediction than generalized approac...
Evaluated seizure-detection rate with aEEG in an underserved epilepsy population and how it relates to self-reported seizure control is examined to highlight the importance of objective monitoring beyond patient self-report, particularly in vulnerable populations.
This study systematically introduces and evaluates 25 less-explored time-domain features, 13 of which have no documented precedent as classification features in scalp EEG seizure detection, against 25 classical features and their 50-feature combination.
Findings support the feasibility of seizure monitoring with reduced montages approximating chronic subscalp device geometries, despite the need for improved detection algorithms, and suggest that EMU-based full-montage performance could help identify candidates for these devices.
Epilepsy is a long-lasting neurological condition that is characterized by repeated seizures and affects millions of people across the world. Traditional methods of diagnosis that are based on manual interpretation of the clinical examinations and electroencephalogram (EEG) are frequently time-consuming and subjective....
At least 48-hours of aEEG was highest yield for seizures, and longer studies may be appropriate for people with lower seizure frequency; IEDs were less dependent on study length and were more associated with pre-aEEG certainty of epilepsy diagnosis.
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