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Monitoring the Burden of Seizures and Highly Epileptiform Patterns in Critical Care with a Novel Machine Learning Method.

Baharan KamousiSuganya KarunakaranKapil GururanganMatthew MarkertBarbara DeckerPouya KhankhanianLaura MainardiJames QuinnRaymond WooJosef Parvizi
Published in: Neurocritical care (2020)
Ruling out seizures accurately in a large proportion of cases can help prevent unnecessary or aggressive over-treatment in critical care settings, where empiric treatment with antiseizure medications is currently prevalent. Claritγ's high sensitivity for SE and high negative predictive value for cases without epileptiform activity make it a useful tool for triaging treatment and the need for urgent neurological consultation.
Keyphrases
  • machine learning
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  • risk factors
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  • blood brain barrier
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  • big data
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