2020
Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification
Zhang F, Dvornek N, Yang J, Chapiro J, Duncan J. Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification. IEEE Transactions On Medical Imaging 2020, 39: 3331-3342. PMID: 32356739, PMCID: PMC7606489, DOI: 10.1109/tmi.2020.2990625.Peer-Reviewed Original ResearchConceptsConvolutional neural networkNeural networkClassification taskProbability calibrationTissue classification tasksImage representationBaseline methodsPublic datasetsModel performanceRandom forest modelNetworkBetter performanceForest modelDatasetClassificationTaskCT imagesImagesOriginal model outputMR imagesModel outputInstitutional datasetPerformanceEmbeddingOutput
2018
Prediction 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