2021
Identification of Binge Drinkers via Convolutional Neural Network and Support Vector Machine
Li G, Du S, Niu J, Zhang Z, Gao T, Tang X, Wang W, Li C. Identification of Binge Drinkers via Convolutional Neural Network and Support Vector Machine. 2021, 00: 715-720. DOI: 10.1109/icma52036.2021.9512720.Peer-Reviewed Original ResearchConvolutional neural networkNeural networkGray matter volumeSVM modelSupport vector machineNon-binge drinkersVector machine modelDeep learningVector machinePsychosocial measuresTraining samplesBinge drinkingYoung adult binge drinkingMachine modelAdult binge drinkingHuman Connectome ProjectNetworkPsychosocial markersClassificationConnectome ProjectBinge drinkersCortical thicknessMatter volumeBingeVolumetric differences
2017
Classification of Cocaine Dependents from fMRI Data Using Cluster-Based Stratification and Deep Learning
Santos J, Savii R, Ide J, Li C, Quiles M, Basgalupp M. Classification of Cocaine Dependents from fMRI Data Using Cluster-Based Stratification and Deep Learning. Lecture Notes In Computer Science 2017, 10404: 298-313. DOI: 10.1007/978-3-319-62392-4_22.Peer-Reviewed Original ResearchDeep learningDeep learning methodsDeep neural networksDeep belief networkSmall data setsComputational visionClassification of pathologiesBelief networkFMRI classificationVoice recognitionNeural networkLearning methodsRobust trainingBrain decodingSmall dataData setsLearningCocaine dependenceNovel stratification methodTraditional techniquesNetworkClassificationCocaine dependentsNon-addicted individualsDrug use
2016
Information Fusion for Cocaine Dependence Recognition Using fMRI
Faria F, Cappabianco F, Li C, Ide J. Information Fusion for Cocaine Dependence Recognition Using fMRI. 2016, 1107-1112. DOI: 10.1109/icpr.2016.7899784.Peer-Reviewed Original ResearchDistinct feature setsInformation fusion approachEnsemble of classifiersInformation fusionFeature extractionFMRI classificationFeature setsFusion approachArt methodsClassification accuracyExtensive evaluationFinal accuracyNew featuresExperimental resultsTraditional methodologiesClassificationAccuracyPattern analysisClassifierHuman lifeMulti-voxel pattern analysisConnectivity measuresPowerful toolMethodologyRecognition