2024
A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis
Vu T, Yang H, Laport F, Gabrielson B, Calhoun V, Adalı T. A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis. 2024, 00: 1831-1835. DOI: 10.1109/icassp48485.2024.10447397.Peer-Reviewed Original ResearchJoint blind source separationSource separationMulti-subject functional magnetic resonance imagingBlind source separationLatent sourcesSeparation of sourcesDemixing vectorsComputational complexityCompetitive performanceMultiple datasetsEstimation performanceDatasetSource templateMulti-subjectNumerical resultsEfficient methodRuntimeComponent analysisScalable methodPerformanceAlgorithmAnalytical solutionMethodOptimizationImplementation
2023
Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance
Ellis C, Miller R, Calhoun V. Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance. 2023, 00: 1-4. DOI: 10.1109/isbi53787.2023.10230384.Peer-Reviewed Original ResearchClinical decision support systemsDynamic functional network connectivityDeep learning classifier’s performanceDisorder subtypesDeep learning classifierDecision support systemClassifier performanceLearning classifiersNetwork connectivityClassifierFunctional network connectivitySupport systemSchizophrenia subtypesStudy disordersPerformanceDisordersSchizophreniaSubtypesNeuropsychiatricSystemNeuroimagingSubtype-dependentCapability