Automatic Retrieval of EEG Cohorts

The goal of this work is the development of a clinically evaluated patient cohort retrieval system operating on the world’s largest publicly available annotated EEG signal corpus, the TUH EEG Corpus. To aid in the completion of this work, we will develop high-performance, Big-Data software to allow the rapid development of new biomedical applications utilizing dense data. For the purposes of this work, these tools will be used to automatically identify clinical events; considering medical concepts, spatial data and temporal data.

Acknowledgments:

  • This work is a collaboration between the Neural Engineering Data Consortium at Temple University and the Human Language Technology Research Institute at The University of Texas at Dallas.
  • This work is funded by the National Human Genome Research Institute of the NIH under award number 1U01HG008468.
  • The TUH EEG Corpus development was sponsored by the Defense Advanced Research Projects Agency (DARPA), Temple University’s College of Engineering and Office of Research.

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