Automatic Discovery of EEG Cohorts From Clinical Records
Electronic medical records (EMRs) collected at every hospital in the
country collectively contain a staggering wealth of biomedical knowledge.
This information could be transformative if properly harnessed. Our focus
in this research project is the automatic interpretation of a clinical
EEG BigData resource known as the TUH EEG Corpus (TUH EEG). Clinicians
can retrieve relevant EEG signals and EEG reports using standard queries
(e.g. “Young patients with focal cerebral dysfunction who were treated
An important outcome is the existence of an annotated BigData archive of EEGs that will greatly increase accessibility for non-experts in neuroscience, bioengineering and medical informatics who would like to study EEG data. The creation of this resource through the development of efficient automated data wrangling techniques demonstrates that a much wider range of BigData bioengineering applications are now tractable.