Attention-Based Network for Weak Labels in Neonatal Seizure Detection.

ABSTRACT: Seizures are a common emergency in the neonatal intesive care unit (NICU) among newborns receiving therapeutic hypothermia for hypoxic ischemic encephalopathy. The high incidence of seizures in this patient population necessitates continuous electroencephalographic (EEG) monitoring to detect and treat them. Due to EEG recordings being reviewed intermittently throughout the day, inevitable delays to seizure identification and treatment arise. In recent years, work on neonatal seizure detection using deep learning algorithms has started gaining momentum. These algorithms face numerous challenges: first, the training data for such algorithms comes from individual patients, each with varying levels of label imbalance since the seizure burden in NICU patients differs by several orders of magnit

SUBMITTER: Isaev DY 

PROVIDER: S-EPMC7521836 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature