Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence
Tveit J, Aurlien H, Plis S, Calhoun V, Tatum W, Schomer D, Arntsen V, Cox F, Fahoum F, Gallentine W, Gardella E, Hahn C, Husain A, Kessler S, Kural M, Nascimento F, Tankisi H, Ulvin L, Wennberg R, Beniczky S. Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence. JAMA Neurology 2023, 80: 805-812. PMID: 37338864, PMCID: PMC10282956, DOI: 10.1001/jamaneurol.2023.1645.Peer-Reviewed Original ResearchMeSH KeywordsAdultArtificial IntelligenceElectroencephalographyEpilepsyHumansMaleNeural Networks, ComputerReproducibility of ResultsConceptsPublishing AI modelsAI modelsArtificial intelligenceTesting data setsHuman expertsAutomated interpretationConvolutional neural network modelHuman expert level performanceElectroencephalogram data setsData setsRoutine electroencephalogramNeural network modelExpert-level performanceMulticenter diagnostic accuracy studyReference standardAbnormal EEG recordingsVideo-EEG recordingsDetection of epileptiform abnormalitiesRecords of patientsReceiver operating characteristic curveSingle-center dataArea under the receiver operating characteristic curveDevelopment dataDiagnostic accuracy studiesNetwork model