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Recent News
(20170629) Today, the research team celebrated the departure of two significant graduates, Silvia Lopez and Aaron Gross, over lunch. Prior to lunch, Silvia gave an outstanding presentation on her thesis proposal, found here .
(20170621) The Research Team has submitted their paper in the NIPS2017 conference, titled "Deep Architectures for Automated Seizure Detection in Scalp EEGs" ...Continue Reading

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 with Topamax”).

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.