Automated detection of immune effector cell-associated neurotoxicity syndrome (ICANS) via quantitative EEG

This dataset and accompanying code support the reproduction of results
reported in [Eckhardt, Sun, Malik, et al., "Automated detection of immune
effector cell-associated neurotoxicity syndrome via quantitative EEG," _Ann
Clin Transl Neurol_ 2023;10(10):1776 -1789 (PMID
37545104)](https://pubmed.ncbi.nlm.nih.gov/37545104/). In that study, we
developed the EEG immune effector cell-associated neurotoxicity syndrome
(E-ICANS) score, a machine learning-derived metric for automated detection of
the presence and severity of neurotoxicity among patients receiving chimeric
antigen receptor (CAR)-T cell therapy. The model was trained and evaluated on
a retrospective cohort of CAR-T recipients monitored with continuous EEG at
two tertiary care centers (2016-2020) and demonstrated high criterion,
construct, and predictive validity. The dataset includes quantitative EEG
features, clinical variables, neurotoxicity grades, and associated outcomes.
Code for model training, evaluation, and figure generation is provided to
enable full reproduction of the published analyses.