Accuracy of a Rapid-Response EEG's Automated Seizure-Burden Estimator
This study provides Class II evidence that ASBE software can reliably exclude ESE (98% negative predictive value using a <10% burden cutoff) without expert review in most patients requiring rapid response EEG.
Authors
- Michael Fong (ORCID: https://orcid.org/0000-0002-0874-7059)
- Emily J. Gilmore (ORCID: https://orcid.org/0000-0002-4659-6861)
- Monica B. Dhakar (ORCID: https://orcid.org/0000-0001-9275-2784)
- Gamaleldin Osman (ORCID: https://orcid.org/0000-0002-2231-2473)
- Moshe Mizrahi
- Neishay Ayub (ORCID: https://orcid.org/0000-0001-5490-8776)
- Ji Yeoun Yoo (ORCID: https://orcid.org/0000-0001-7242-9779)
- Brandon Foreman (ORCID: https://orcid.org/0000-0002-5418-674X)
- Sarah E. Schmitt (ORCID: https://orcid.org/0000-0003-1384-9794)
- Lawrence J. Hirsch (ORCID: https://orcid.org/0000-0002-6333-832X)
- Zubeda Sheikh (ORCID: https://orcid.org/0000-0002-0857-7993)
- Ioannis Karakis (ORCID: https://orcid.org/0000-0001-5122-7211)
- Hiba A. Haider (ORCID: https://orcid.org/0000-0001-7118-3690)
- Wei Fang (ORCID: https://orcid.org/0000-0001-8139-1119)
- Janine Molino
Institutions
- Emory University (US)
- Medical University of South Carolina (US)
- Virginia Commonwealth University (US)
- Brown University (US)
- Westmead Hospital (AU)
- Yale University (US)
- University of Chicago (US)
- Mayo Clinic in Arizona (US)
- Xenon Pharmaceuticals (Canada) (CA)
- University of Cincinnati (US)
- Icahn School of Medicine at Mount Sinai (US)
Publication Details
- Journal
- Neurology
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1212/wnl.0000000000210234
- Citations
- 5
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.71