2025
Spatiotemporal Learning with Context-Aware Video Tubelets for Ultrasound Video Analysis
Li G, Chen L, Hicks B, Schnittke N, Kessler D, Shunp J, Parker M, Baloescu C, Moore C, Gregory C, Gregory K, Raju B, Kruecker J, Chen A. Spatiotemporal Learning with Context-Aware Video Tubelets for Ultrasound Video Analysis. 2025, 00: 1-5. DOI: 10.1109/isbi60581.2025.10981242.Peer-Reviewed Original ResearchGlobal spatial contextState-of-the-art methodsAligned feature mapState-of-the-artUltrasound video analysisReal-time workflowsComplex spatiotemporal informationContext-awarenessFeature mapsObject detectionFive-fold cross-validationSpatiotemporal learningComputational complexityDetection algorithmDetected ROIsSpatial contextUltrasound videosSpatiotemporal featuresSpatiotemporal informationTubeletsVideoVideo analysisClas-sificationReceptive fieldsClassifier
2024
Recurrence solution of monomer-polymer models on two-dimensional rectangular lattices
Kong Y. Recurrence solution of monomer-polymer models on two-dimensional rectangular lattices. Physical Review E 2024, 110: 054135. PMID: 39690661, DOI: 10.1103/physreve.110.054135.Peer-Reviewed Original ResearchTwo-dimensional rectangular latticeRecurrence relationsRectangular latticeMonomer-dimer problemPlanar latticesRecurrent solutionsLong standing problemLattice sitesAdjacent lattice sitesLatticeProblemComputational complexitySolutionRelationsEnumerationPolymer coverUnoccupied lattice sitesRigid polymersMonomer-polymerSolution of long-standing problemsPolymerPolymer lengthEvolutionary Strategies Enable Systematic and Reliable Uncertainty Quantification: A Proof-of-Concept Pilot Study on Resting-State Functional MRI Language Lateralization
Stember J, Dishner K, Jenabi M, Pasquini L, K Peck K, Saha A, Shah A, O’Malley B, Ilica A, Kelly L, Arevalo-Perez J, Hatzoglou V, Holodny A, Shalu H. Evolutionary Strategies Enable Systematic and Reliable Uncertainty Quantification: A Proof-of-Concept Pilot Study on Resting-State Functional MRI Language Lateralization. Journal Of Imaging Informatics In Medicine 2024, 38: 576-586. PMID: 38980624, PMCID: PMC11810852, DOI: 10.1007/s10278-024-01188-6.Peer-Reviewed Original ResearchOut-of-distributionDeep neuroevolutionArtificial intelligenceOut-of-distribution imagesTrustworthy artificial intelligenceTest set accuracyUncertainty quantificationComputational complexityEffective uncertainty quantificationAleatoric uncertaintyDistribution entropyMedical diagnosisUQ methodsRadiology applicationsClinical workflowOptimal strategyEnablersNeuroevolutionExpert reviewUQ approachEnsembleExpert assessmentIntelligenceMapsModel ensembleA Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis
Vu T, Yang H, Laport F, Gabrielson B, Calhoun V, Adalı T. A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis. 2024, 00: 1831-1835. DOI: 10.1109/icassp48485.2024.10447397.Peer-Reviewed Original ResearchJoint blind source separationSource separationMulti-subject functional magnetic resonance imagingBlind source separationLatent sourcesSeparation of sourcesDemixing vectorsComputational complexityCompetitive performanceMultiple datasetsEstimation performanceDatasetSource templateMulti-subjectNumerical resultsEfficient methodRuntimeComponent analysisScalable methodPerformanceAlgorithmAnalytical solutionMethodOptimizationImplementationMode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis
Gabrielson B, Yang H, Vu T, Calhoun V, Adali T. Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis. IEEE Access 2024, 12: 192356-192376. DOI: 10.1109/access.2024.3517338.Peer-Reviewed Original ResearchTensor decompositionSize of modern datasetsRank-1 tensorsComputational complexity scalesCore tensorTucker decompositionFeature selectionComputational complexitySelection schemeData tensorMultidimensional arraysRank-1CoresetTensor dataMatrix decompositionModern datasetsMassive sizeMyriad of applicationsMethod efficiencyDatasetSelection abilityComplexity scalesMeasure of discrepancyWell-approximatedDecomposition method
2022
Deep-learning-based methods of attenuation correction for SPECT and PET
Chen X, Liu C. Deep-learning-based methods of attenuation correction for SPECT and PET. Journal Of Nuclear Cardiology 2022, 30: 1859-1878. PMID: 35680755, DOI: 10.1007/s12350-022-03007-3.Peer-Reviewed Original ResearchConceptsHigh computational complexityAC strategyNeural networkRaw emission dataComputational complexityLearning methodsCT imagesΜ-mapsPET imagesLow accuracySuperior performanceImagesAttenuation correctionPromising resultsMR imagesAttenuation mapPET/CT scannerHigh noise levelsArtifactsNetworkCT artifactsPET/MRI scannerIntermediate stepComplexityScanner
2021
Conditional score matching for high-dimensional partial graphical models
Fan X, Zhang Q, Ma S, Fang K. Conditional score matching for high-dimensional partial graphical models. Computational Statistics & Data Analysis 2021, 153: 107066. DOI: 10.1016/j.csda.2020.107066.Peer-Reviewed Original ResearchConditional scoreComputational complexityMore general distributionsEffective computational algorithmGraphical modelsStatistical propertiesHigh computational costPartial graphsComputational algorithmComputational costNormalization constantsBreast cancer gene expression datasetsGeneral distributionNetwork constructionCancer gene expression datasetsMultiplicative normalizationMultivariate data analysisGene expression datasetsCompetitive performanceComplexityGraphData analysisModelConstruction approachExpression datasets
2020
Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty
Li X, Zhou Y, Dvornek NC, Gu Y, Ventola P, Duncan JS. Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty. Lecture Notes In Computer Science 2020, 12261: 792-801. PMID: 34308439, PMCID: PMC8299327, DOI: 10.1007/978-3-030-59710-8_77.Peer-Reviewed Original ResearchShapley value explanationMedical image dataDeep learning modelsFeature importance estimationImage dataLearning modelComplex deep learning modelsImportance estimationFeature importance resultsShapley value frameworkInput feature importancePublic neuroimaging datasetComputational complexityShapley explanationsFeature importanceUncertainty estimation methodExplanation workParticular predictionNeuroimaging datasetsMedical fieldImportance resultsImpressive powerEstimation methodUnderlying propertiesImportant approach
2019
Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery
Li X, Dvornek NC, Zhou Y, Zhuang J, Ventola P, Duncan JS. Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery. Lecture Notes In Computer Science 2019, 11492: 718-730. PMID: 32982121, PMCID: PMC7519580, DOI: 10.1007/978-3-030-20351-1_56.Peer-Reviewed Original ResearchShapley value explanationAutism spectrum disorderFunctional magnetic resonance imagingDeep learning modelsDeep learning classifierCooperative game theoryLearning modelLearning classifiersGraph structureRandom forestGame theoryMachine learning methodsMNIST datasetTraditional learning strategiesSpectrum disorderFMRI biomarkersComputational complexityLearning methodsHuman perceptionHierarchical pipelineFeature importanceN featuresLearning strategiesInput dataEfficient interpretation
2018
Modeling hybrid traits for comorbidity and genetic studies of alcohol and nicotine co-dependence
Zhang H, Liu D, Zhao J, Bi X. Modeling hybrid traits for comorbidity and genetic studies of alcohol and nicotine co-dependence. The Annals Of Applied Statistics 2018, 12: 2359-2378. PMID: 30666272, PMCID: PMC6338437, DOI: 10.1214/18-aoas1156.Peer-Reviewed Original ResearchFull likelihoodComplicated likelihood functionsParametric frameworkParametric modeling frameworkHigh computational complexityExtensive simulation studyModel fitting algorithmStatistical inferenceRank-based methodLikelihood functionComputational burdenType I error ratesComputational complexityFitting algorithmSimulation studyNovel multivariate modelModeling frameworkEffect size estimationLatent variablesHybrid modelInferenceSize estimationModelFrameworkTheory
2017
modSaRa: a computationally efficient R package for CNV identification
Xiao F, Niu Y, Hao N, Xu Y, Jin Z, Zhang H. modSaRa: a computationally efficient R package for CNV identification. Bioinformatics 2017, 33: 2384-2385. PMID: 28453611, PMCID: PMC5860124, DOI: 10.1093/bioinformatics/btx212.Peer-Reviewed Original ResearchConceptsComputational complexityHigh computational complexityR packageOptimal computational complexityUser-friendly R packageEfficient R packageSupplementary dataCurrent versionComputational algorithmDesirable accuracyComplexityPackageComprehensive toolCNV identificationDownloadAlgorithmVariant identificationBioinformaticsImplementationTypes of variationRCPPAccuracyIntegrationStepTool
2015
VERTIcal Grid lOgistic regression (VERTIGO)
Li Y, Jiang X, Wang S, Xiong H, Ohno-Machado L. VERTIcal Grid lOgistic regression (VERTIGO). Journal Of The American Medical Informatics Association 2015, 23: 570-579. PMID: 26554428, PMCID: PMC4901373, DOI: 10.1093/jamia/ocv146.Peer-Reviewed Original ResearchConceptsFederated data analysisReal-world medical classification problemsMedical classification problemsLogistic regression algorithmAccurate global modelData setsReal data setsClassification problemExchange of informationLR problemTime complexityComputational complexityExpensive operationRegression algorithmComputational costData analysisAlgorithmDual optimizationTechnical challengesLarge amountComplexityPatient recordsLR modelNovel techniqueHessian matrix
2013
Genome Sequence Compression with Distributed Source Coding
Wang S, Jiang X, Cui L, Dai W, Deligiannis N, Li P, Xiong H, Cheng S, Ohno-Machado L. Genome Sequence Compression with Distributed Source Coding. 2013, 525-525. DOI: 10.1109/dcc.2013.104.Peer-Reviewed Original ResearchEncoder sideSource codingFile sizeLow processing capabilitiesHigh computational complexityLimited communication bandwidthFile size reductionLow-density parity-check (LDPC) decodersCompression frameworkHash codingBandwidth usageCommunication bandwidthParity-check decoderSequence compressionCompression techniquesAdaptive code lengthComputational complexityProcessing capabilitiesSmall storageMemory requirementsGenome compressionFactor graphGenome dataCode lengthCoding
2012
Calibrating predictive model estimates to support personalized medicine
Jiang X, Osl M, Kim J, Ohno-Machado L. Calibrating predictive model estimates to support personalized medicine. Journal Of The American Medical Informatics Association 2012, 19: 263-274. PMID: 21984587, PMCID: PMC3277613, DOI: 10.1136/amiajnl-2011-000291.Peer-Reviewed Original ResearchConceptsReal-world medical classification problemsMedical classification problemsClassification problemPredictive model estimatesComputational complexityACP algorithmIsotonic regressionPredictive modelTerms of areaImportant performance measuresCalibration methodAdaptive techniqueCalculation of CIsAdaptive calibrationSquared errorIndividual predictionsPerformance measuresFit testInformationNew calibration methodCurrent methods
2009
Integrating Sequencing Technologies in Personal Genomics: Optimal Low Cost Reconstruction of Structural Variants
Du J, Bjornson RD, Zhang ZD, Kong Y, Snyder M, Gerstein MB. Integrating Sequencing Technologies in Personal Genomics: Optimal Low Cost Reconstruction of Structural Variants. PLOS Computational Biology 2009, 5: e1000432. PMID: 19593373, PMCID: PMC2700963, DOI: 10.1371/journal.pcbi.1000432.Peer-Reviewed Original ResearchConceptsDifferent read lengthsDifferent technologiesSemi-realistic simulationComputational complexityMaximum accuracyAssembly algorithmReconstruction efficiencySimulation toolboxPersonal genomicsAccurate detectionLow costChallenging stepTechnologyCostAlgorithmAccurate assemblyComplexitySmall enough scalesReconstructionGoalIndividual genomesCanonical problemImportant goalToolboxSimulations
2007
Computational Bayesian inference for estimating the size of a finite population
Nandram B, Zelterman D. Computational Bayesian inference for estimating the size of a finite population. Computational Statistics & Data Analysis 2007, 51: 2934-2945. DOI: 10.1016/j.csda.2006.11.034.Peer-Reviewed Original ResearchPosterior distributionComputational Bayesian inferenceBayesian log-linear modelsDiffuse prior distributionIntensive Bayesian methodsFinite populationMetropolis algorithmMarkov chainPrior distributionBayesian inferenceBayesian methodsComputational complexityLog-linear modelMarginal probabilitiesClosed populationAdministrative listsDistributionInferenceAlgorithmProbabilityPerceived object trajectories during occlusion constrain visual statistical learning
Fiser J, Scholl BJ, Aslin RN. Perceived object trajectories during occlusion constrain visual statistical learning. Psychonomic Bulletin & Review 2007, 14: 173-178. PMID: 17546749, DOI: 10.3758/bf03194046.Peer-Reviewed Original ResearchConceptsVisual statistical learningStatistical learningLearning phaseDifferential eye movementsPerceptual biasesFamiliarity judgmentsShape pairsEye movementsObject trajectoriesPerceptShape sequenceLearningParticipantsComputational complexityJudgmentsObject transitionsBiasesTrajectoriesSpeed profileBiasObjectsOccluderContextFindings
1993
The fast multipole method for the wave equation: a pedestrian prescription
Coifman R, Rokhlin V, Wandzura S. The fast multipole method for the wave equation: a pedestrian prescription. IEEE Antennas And Propagation Magazine 1993, 35: 7-12. DOI: 10.1109/74.250128.Peer-Reviewed Original ResearchThe fast multipole method for electromagnetic scattering calculations
Coifman R, Rokhlin V, Wandzura S. The fast multipole method for electromagnetic scattering calculations. 1993, 48-51 vol.1. DOI: 10.1109/aps.1993.385405.Peer-Reviewed Original ResearchFast multipole methodMultipole methodDense impedance matrixThree-dimensional electromagnetic problemsBoundary integral equationsAccurate numerical modelingMethod of momentsIntegral equationsElectromagnetic problemsElectromagnetic scattering calculationsRadiation problemsElementary derivationPhysical interpretationImpedance matrixComputational complexityElectromagnetic scatteringScattering calculationsNumerical modelingSparse decompositionEquationsProblemDerivationMomentModelingCalculations
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