The Temple University Hospital Seizure Detection Corpus
Vinit Shah, Eva von Weltin, Silvia Lopez, James Riley McHugh, Lily Veloso, Meysam Golmohammadi, Iyad Obeid, Joseph Picone
arXiv:1801.08085v1283 citationsHas Code
AI Analysis
This provides a new dataset for researchers in medical AI and neurology, but it is incremental as it focuses on data creation rather than novel methods.
The authors introduced the TUH EEG Seizure Corpus (TUSZ), the largest open-source corpus for seizure detection, and described its development techniques and effectiveness evaluation.
We introduce the TUH EEG Seizure Corpus (TUSZ), which is the largest open source corpus of its type, and represents an accurate characterization of clinical conditions. In this paper, we describe the techniques used to develop TUSZ, evaluate their effectiveness, and present some descriptive statistics on the resulting corpus.