2024
A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks
Batta I, Abrol A, Calhoun V. A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks. 2024, 00: 1-6. DOI: 10.1109/ciss59072.2024.10480204.Peer-Reviewed Original ResearchLearning frameworkBrain subsystemsSubspace learning frameworkBrain networksHigh-dimensional neuroimaging dataConvolutional neural networkLow-dimensional subspaceSupervised learning approachDeep learning frameworkStructural brain featuresPredictive performanceUnsupervised approachNeural networkAutomated frameworkDimensional subspaceAlzheimer's diseaseLearning approachBrain changesFeature importanceTraining procedureNeuroimaging dataBrain featuresSalient networkNetworkBrain disorders
2023
An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis
Sattiraju A, Ellis C, Miller R, Calhoun V. An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis. 2023, 00: 255-259. DOI: 10.1109/bibe60311.2023.00048.Peer-Reviewed Original ResearchConvolutional neural networkRobust deep learning approachBaseline convolutional neural networkChannel lossDeep learning methodsDeep learning modelsDeep learning approachDecision support roleExplainability approachesClassifier performanceRobust modelNeural networkExplainable modelsLearning methodsLearning approachLearning modelsAutomated diagnosisImplementation environmentEEG dataDiagnosis of SZExplainabilityRaw EEGTest dataRobustnessBiomarkers of SZMulti-scale convolutional recurrent neural network for psychiatric disorder identification in resting-state EEG
Yan W, Yu L, Liu D, Sui J, Calhoun V, Lin Z. Multi-scale convolutional recurrent neural network for psychiatric disorder identification in resting-state EEG. Frontiers In Psychiatry 2023, 14: 1202049. PMID: 37441141, PMCID: PMC10333510, DOI: 10.3389/fpsyt.2023.1202049.Peer-Reviewed Original ResearchConvolutional recurrent neural networkRecurrent neural networkResting-state EEGNeural networkPsychiatric disordersDeep learning classification modelLow-dimensional subspaceTwo-class classificationDesigning individualized treatmentLearning classification modelsEEG backgroundClassification modelHealthy controlsDepressive disorderSpatiotemporal informationClinical observationsDisease severityAccurate classificationIndividualized treatmentBiomarkersDisorder classificationDisorder identificationDisordersClassificationNeuroimaging biomarkersEffective Training Strategy for NN Models of Working Memory Classification with Limited Samples
Suresh P, Ray B, Thapaliya B, Farahdel B, Kazemivash B, Chen J, Duan K, Calhoun V, Liu J. Effective Training Strategy for NN Models of Working Memory Classification with Limited Samples. 2023, 00: 1-4. DOI: 10.1109/isbi53787.2023.10230722.Peer-Reviewed Original ResearchTraining strategyNeural networkData-hungry techniquesNN modelImage featuresSets of hyperparametersMachine learning methodsMachine learning modelsTrained NN modelModel performanceHigh memory capacityImbalanced samplesLearning methodsMemory capacityBrain imaging featuresSuboptimal solutionLearning modelsNetwork configurationEffective training strategyEfficient reuseWorking memory capacityTask-specificData conditionsBiomedical imagingNetworkNovel methods for elucidating modality importance in multimodal electrophysiology classifiers
Ellis C, Sendi M, Zhang R, Carbajal D, Wang M, Miller R, Calhoun V. Novel methods for elucidating modality importance in multimodal electrophysiology classifiers. Frontiers In Neuroinformatics 2023, 17: 1123376. PMID: 37006636, PMCID: PMC10050434, DOI: 10.3389/fninf.2023.1123376.Peer-Reviewed Original ResearchExplainability approachesExplainability methodsAutomated sleep stage classificationRaw time series dataConvolutional neural networkDeep learning classifierSleep stage classificationNovel methodMultimodal classificationLearning classifiersNeural networkClassifierLocal explanationsGlobal explanationsExplainabilitySubject-level differencesTime series dataAdvancement of personalized medicineGlobal methodClinical classifierClassificationClinical variablesElectrophysiological studiesStage classificationElectrophysiological classification