Response to “Gaining Clarity on the Claritɣ Algorithm”
Author:
Publisher
Springer Science and Business Media LLC
Subject
Critical Care and Intensive Care Medicine,Neurology (clinical)
Link
https://link.springer.com/content/pdf/10.1007/s12028-023-01798-y.pdf
Reference7 articles.
1. Parvizi J, Gururangan K, Knickerbocker D, Kamousi B, Woo R. Gaining clarity on the Clarity algorithm. Neurocrit Care. 2023. https://doi.org/10.1007/s12028-023-01797-z.
2. Villamar MF, Ayub N, Koenig SJ. automated seizure detection in patients with cardiac arrest: a retrospective review of Ceribell rapid-EEG recordings. Neurocrit Care. 2023. https://doi.org/10.1007/s12028-023-01681-w.
3. Kamousi B, Karunakaran S, Gururangan K, et al. Monitoring the burden of seizures and highly epileptiform patterns in critical care with a novel machine learning method. Neurocrit Care. 2021;34:908–17.
4. Payne ET, Zhao XY, Frndova H, et al. Seizure burden is independently associated with short term outcome in critically ill children. Brain. 2014;137:1429–38.
5. Hirsch LJ, Fong MWK, Leitinger M, et al. American Clinical Neurophysiology Society’s standardized critical care EEG terminology: 2021 version. J Clin Neurophysiol. 2021;38:1–29.
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