Resources

Deidentified seizure and ictal-interictal continuum (IIC) data extracted from 156,582 EEG reports across three health systems (two adult, one pediatric), plus the LLM-based extraction pipeline. Companion to Sartipi et al. (IJMI, under review).

Data and code from Kong et al. (Epilepsia 2025): 1,542 expert and non-expert participants annotated 478,834 EEG epochs for seizures and rhythmic/periodic patterns; mixed-effects analyses compare crowd vs expert accuracy.

Data and code to reproduce this paper: https://pmc.ncbi.nlm.nih.gov/articles/PMC9847346/

TEEGLLTEEG

Cyclops dataset

This dataset supports a published prospective cohort study using machine learning to develop the Visual EEG Confusion Assessment Method Severity (VE-CAM-S) scale for quantifying delirium and coma severity.

Data and code to automatically detect periods of suppression in critically ill ICU patients.

Multicenter clinical and EEG Database including patients who were comatose after cardiac arrest. This database includes 1,020 patients and more than 50,000 hours of continuous EEG from 7 hospitals in the U.S. and Europe.

ELUCID is a 7-center longitudinal study of 600 adults aged 55+ with late-onset unexplained epilepsy, building a multimodal biorepository (brain MRI, overnight EEG, cognitive testing, blood biomarkers) to identify risk factors for dementia.

De-identified data and a PK-PD + MALTS causal-inference pipeline reproducing the effect of untreated epileptiform-activity burden on poor discharge outcome in critically ill patients (Parikh et al., Lancet Digital Health 2023).