DynamoSort: Using machine learning approaches for the automatic classification of seizure dynamotypes.

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Bibliographic Details
Title: DynamoSort: Using machine learning approaches for the automatic classification of seizure dynamotypes.
Authors: Wooley J; School of Biomedical Engineering, University of Sydney, Sydney, Australia., Zachery-Savella A; Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, USA., Le M; Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, USA., Scofield S; Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, USA., Jay K; Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, USA., Mosse-Robinson J; School of Biomedical Engineering, University of Sydney, Sydney, Australia., West PJ; Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, USA., Wilcox KS; Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, USA., Anderson DN; School of Biomedical Engineering, University of Sydney, Sydney, Australia.; Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, USA.; Department of Neurosurgery, University of Utah, Salt Lake City, UT.
Source: BioRxiv : the preprint server for biology [bioRxiv] 2025 Feb 17. Date of Electronic Publication: 2025 Feb 17.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2692-8205
DOI:10.1101/2025.02.12.637999