2024
Imaging‐genomic spatial‐modality attentive fusion for studying neuropsychiatric disorders
Rahaman A, Garg Y, Iraji A, Fu Z, Kochunov P, Hong L, Van Erp T, Preda A, Chen J, Calhoun V. Imaging‐genomic spatial‐modality attentive fusion for studying neuropsychiatric disorders. Human Brain Mapping 2024, 45: e26799. PMID: 39562310, PMCID: PMC11576332, DOI: 10.1002/hbm.26799.Peer-Reviewed Original ResearchConceptsNeural networkDilated convolutional neural networkJoint learning frameworkAttention scoresState-of-the-artDeep neural networksNeural network decisionsConvolutional neural networkAttention fusionFusion moduleDiverse data sourcesArtificial intelligence modelsLearning frameworkAttention moduleJoint learningMultimodal clusteringNetwork decisionsInput streamMultimodal learningHigh-dimensionalIntermediate fusionFused dataSZ classificationIntelligence modelsContextual patternsAltmetric Attention Scores and Citations of Published Research With or Without Preprints
Zissette S, Gautam A, Krumholz H, Ross J, Wallach J. Altmetric Attention Scores and Citations of Published Research With or Without Preprints. JAMA Network Open 2024, 7: e2424732. PMID: 39058492, PMCID: PMC11282438, DOI: 10.1001/jamanetworkopen.2024.24732.Peer-Reviewed Original Research
2023
Is Attention Interpretation? A Quantitative Assessment on Sets
Haab J, Deutschmann N, Martínez M. Is Attention Interpretation? A Quantitative Assessment on Sets. Communications In Computer And Information Science 2023, 1752: 303-321. DOI: 10.1007/978-3-031-23618-1_21.Peer-Reviewed Original ResearchBinary classification problemInterpretation of attentionClassification problemAttention mechanismSynthetic datasetsUnordered collectionClassification performanceSilent failuresMachine learningGlobal labelsData modalitiesIndividual instancesAttention distributionAttention scoresAttention patternsData pointsSub-componentsInstancesDataset
2018
Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies
Fong AHC, Yoo K, Rosenberg MD, Zhang S, Li CR, Scheinost D, Constable RT, Chun MM. Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies. NeuroImage 2018, 188: 14-25. PMID: 30521950, PMCID: PMC6401236, DOI: 10.1016/j.neuroimage.2018.11.057.Peer-Reviewed Original ResearchConceptsAttention task performanceDynamic functional connectivityTask performanceIndividual differencesExecutive control brain networksFunctional connectivityFunctional brain scansAttention performanceTask conditionsAttention scoresBrain networksFMRI dataBrain regionsBetter attentionFC featuresFC matricesDFC matrixPearson's rAttentionIndividualsOne-subjectBrain scansConnectivityConnectomeCross-validation approach
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