2020
Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings
Payabvash S, Aboian M, Tihan T, Cha S. Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings. Frontiers In Oncology 2020, 10: 71. PMID: 32117728, PMCID: PMC7018938, DOI: 10.3389/fonc.2020.00071.Peer-Reviewed Original ResearchDecision tree modelDifferent machineTree modelAccurate classification rateAveraged AUCClassification algorithmsTraining datasetRandom forestDecision treeClassification rateRandom forest modelMachineAlgorithmTerminal nodesHigh accuracyForest modelDecision modelHistogram analysisDichotomized classificationClassificationIntra-axial posterior fossa tumorsAccuracyDatasetGreater accuracyNodes
2019
Diffusion tensor tractography in children with sensory processing disorder: Potentials for devising machine learning classifiers
Payabvash S, Palacios EM, Owen JP, Wang MB, Tavassoli T, Gerdes M, Brandes-Aitken A, Marco EJ, Mukherjee P. Diffusion tensor tractography in children with sensory processing disorder: Potentials for devising machine learning classifiers. NeuroImage Clinical 2019, 23: 101831. PMID: 31035231, PMCID: PMC6488562, DOI: 10.1016/j.nicl.2019.101831.Peer-Reviewed Original ResearchConceptsPosterior white matter tractsSupport vector machineAccurate classification rateNaïve BayesDifferent machineNeural networkVector machineRandom forestClassification rateRandom forest modelMachineEdge densityConnectivity metricsAlgorithmDTI/High accuracyForest modelMetricsAccuracyBrain's inabilityBayesClassifierNetworkSensory processing disordersClassification