Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks
Qu G, Orlichenko A, Wang J, Zhang G, Xiao L, Zhang K, Wilson T, Stephen J, Calhoun V, Wang Y. Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. IEEE Transactions On Medical Imaging 2024, 43: 1568-1578. PMID: 38109241, PMCID: PMC11090410, DOI: 10.1109/tmi.2023.3343365.Peer-Reviewed Original ResearchConceptsGraph transformation frameworkBrain imaging datasetsFunctional brain networksPhiladelphia Neurodevelopmental CohortConvolutional deep learningFeature embeddingPropagation weightsGraph embeddingHuman Connectome ProjectAttention mechanismImage datasetsDeep learningGraph transformationFunctional connectivityAnalyze functional brain networksTransformation frameworkDiffusion strategyBrain networksPositional encodingSpatial knowledgePrediction accuracyIndividual cognitive abilitiesEmbeddingNetworkGraphMultiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis
Wang W, Xiao L, Qu G, Calhoun V, Wang Y, Sun X. Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis. Medical Image Analysis 2024, 94: 103144. PMID: 38518530, DOI: 10.1016/j.media.2024.103144.Peer-Reviewed Original ResearchConceptsGraph convolutional networkEmbedding learningConvolutional networkIrregular graph-structured dataFunctional connectivity network analysisGraph-structured dataSoft-max classifierHigh-order relationsFunctional connectivity networksHypergraph convolutional networkDiagnosis of brain diseasesClass consistMultiview informationSoft-maxEmbedding spaceModel brain networksHyperedge weightsDiagnosis decisionAutomated diagnosisMultiple verticesEmbeddingFixed weightNetworkConnectivity network analysisFunctional magnetic resonance imaging