AI RESEARCH
Classification of IED-free EEG Responses for Assisted Epilepsy Diagnosis
arXiv CS.LG
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ArXi:2605.22858v1 Announce Type: cross Diagnosing epilepsy is challenging when routine EEGs lack interictal epileptiform discharges (IEDs). Intermittent photic stimulation (IPS) and hyperventilation (HV) can increase diagnostic yield, but their interpretation is subjective. We propose a reproducible pipeline that classifies EEG recordings acquired during stimulation procedures, using machine-learning features spanning temporal, spectral, wavelet, and connectivity domains, and a stacked ensemble to combine complementary feature sets.