2025
Causal Modeling of FMRI Time-Series for Interpretable Autism Spectrum Disorder Classification
Duan P, Dvornek N, Wang J, Staib L, Duncan J. Causal Modeling of FMRI Time-Series for Interpretable Autism Spectrum Disorder Classification. 2025, 00: 1-5. DOI: 10.1109/isbi60581.2025.10980933.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingAutism spectrum disorderState-of-the-art modelsState-of-the-artFMRI time seriesDeep learning classifierDeep learning modelsTime series informationLearning classifiersClassification accuracyNon-linear interactionsMachine learningLeft precuneusRight precuneusABIDE datasetBrain regionsLearning modelsASD populationSpectrum disorderDisorder classificationASD classificationBrain signalsASD biomarkersDevelopmental disordersCorrelation-based models
2023
Copy Number Variation Informs fMRI-Based Prediction of Autism Spectrum Disorder
Dvornek N, Sullivan C, Duncan J, Gupta A. Copy Number Variation Informs fMRI-Based Prediction of Autism Spectrum Disorder. Lecture Notes In Computer Science 2023, 14312: 133-142. PMID: 38371906, PMCID: PMC10868600, DOI: 10.1007/978-3-031-44858-4_13.Peer-Reviewed Original Research
2021
Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge
Schirmer MD, Venkataraman A, Rekik I, Kim M, Mostofsky SH, Nebel MB, Rosch K, Seymour K, Crocetti D, Irzan H, Hütel M, Ourselin S, Marlow N, Melbourne A, Levchenko E, Zhou S, Kunda M, Lu H, Dvornek NC, Zhuang J, Pinto G, Samal S, Zhang J, Bernal-Rusiel JL, Pienaar R, Chung AW. Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. Medical Image Analysis 2021, 70: 101972. PMID: 33677261, PMCID: PMC9115580, DOI: 10.1016/j.media.2021.101972.Peer-Reviewed Original ResearchConceptsAttention-deficit/hyperactivity disorderAutism Brain Imaging Data ExchangeResting-state fMRI time seriesAutism spectrum disorder (ASD) patientsHuman Connectome ProjectADHD modelHyperactivity disorderADHD comorbidityASD classificationConnectome ProjectOpen-source image analysis platformFMRI time seriesBrain connectomicsFunctional connectomicsClassification methodologyLearning challengesOpen-source datasetField of connectomicsParcellation atlasesDisorder patientsImage analysis platformOmission rateParticipantsConnectomicsMICCAI 2019
2018
2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning
Li X, Dvornek NC, Papademetris X, Zhuang J, Staib LH, Ventola P, Duncan JS. 2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2018, 2018: 1252-1255. PMID: 32983370, PMCID: PMC7519578, DOI: 10.1109/isbi.2018.8363798.Peer-Reviewed Original ResearchConvolutional neural networkNeural networkCNN convolutional layerSpatial featuresASD classificationDeep neural networksMean F-scoreTraditional machineFeature learningConvolutional layersInput formatF-scoreClassification modelTemporal informationNetworkWindow parametersImagesClassificationConvolutionalTemporal statisticsMachineLearningFeaturesFormatScheme
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