Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets
Dvornek NC, Yang D, Ventola P, Duncan JS. Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets. Lecture Notes In Computer Science 2018, 11072: 329-337. PMID: 30873514, PMCID: PMC6411297, DOI: 10.1007/978-3-030-00931-1_38.Peer-Reviewed Original ResearchConceptsRecurrent neural networkNeural networkTask fMRI datasetsMedical image analysis problemsSuch deep networksImage analysis problemsTask fMRI scanTypical control subjectsDeep networkDeep learningTraining lossSmall datasetsLarge datasetsNumber of approachesAutism spectrum disorderAnalysis problemDatasetNetworkTraining runsImage analysisGeneralizable modelNon-imaging variablesSpectrum disorderFMRI analysisModel performancePrediction of Severity and Treatment Outcome for ASD from fMRI
Zhuang J, Dvornek NC, Li X, Ventola P, Duncan JS. Prediction of Severity and Treatment Outcome for ASD from fMRI. Lecture Notes In Computer Science 2018, 11121: 9-17. PMID: 32984867, PMCID: PMC7513883, DOI: 10.1007/978-3-030-00320-3_2.Peer-Reviewed Original ResearchFeature selectionMedical image analysis problemsMedical image analysisLimited training examplesImage analysis problemsDimension of dataFeature selection methodHigh-dimensional regression problemsTraining examplesTwo-level approachAccurate predictive modelsRegression problemsHigh dimensionalityLarge databaseRandom forest modelSelection methodNon-linear caseAnalysis problemNumber of voxelsImage analysisForest modelState fMRI datasetsMeans of voxelAccurate modelFMRI datasets