2024
nipalsMCIA: flexible multi-block dimensionality reduction in R via nonlinear iterative partial least squares
Mattessich M, Reyna J, Aron E, Ay F, Kilmer M, Kleinstein S, Konstorum A. nipalsMCIA: flexible multi-block dimensionality reduction in R via nonlinear iterative partial least squares. Bioinformatics 2024, 41: btaf015. PMID: 39799512, PMCID: PMC11783316, DOI: 10.1093/bioinformatics/btaf015.Peer-Reviewed Original ResearchConceptsIterative partial least squaresNonlinear iterative partial least squaresDimensionality reductionMultiple co-inertia analysisJoint dimensionality reductionSignificant speed-upUnsupervised learningSingle-cell datasetsMulti-omics dataCo-inertia analysisFeature dimensionsSpeed-upBioconductor packageSingle-cell analysisPartial least squaresLeast squaresRobust approachImplementationHTMLDatasetBioconductorIdentifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach
Sancho M, Ellis C, Miller R, Calhoun V. Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039893, DOI: 10.1109/embc53108.2024.10781959.Peer-Reviewed Original ResearchConceptsDeep learning approachLearning-based studiesMachine learning methodsMachine learning modelsMachine learning-based studiesExplainability approachesCross-validation foldsLearning methodsLearning approachLearning modelsDevelopment of robust approachesMachineDiagnosis of schizophreniaDiverse symptom presentationsPower dataBiomarkers of SZRobust approachFrequency bandLeft hemisphereSpectral power data
2023
A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy
Deng W, Li B, Wang J, Jiang W, Yan X, Li N, Vukmirovic M, Kaminski N, Wang J, Zhao H. A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy. Briefings In Bioinformatics 2023, 24: bbac616. PMID: 36631398, PMCID: PMC9851324, DOI: 10.1093/bib/bbac616.Peer-Reviewed Original Research
2022
Missing Data
Tong G, Li F, Allen A. Missing Data. 2022, 1681-1701. DOI: 10.1007/978-3-319-52636-2_117.Peer-Reviewed Original ResearchLikelihood-based analysisMissingness modelMissingness processData mechanismAverage treatment effectStatistical methodsComplete case analysisConsistent estimatesRobust approachInverse probability weightingBiased estimatesMissingnessOutcome distributionModeling approachProbability weightingData processSensitivity analysisOutcome modelModelEstimatesBrief discussionPractical considerationsInferenceApproachImputation
2019
Missing Data
Tong G, Li F, Allen A. Missing Data. 2019, 1-21. DOI: 10.1007/978-3-319-52677-5_117-1.Peer-Reviewed Original ResearchLikelihood-based analysisMissingness modelMissingness processData mechanismAverage treatment effectStatistical methodsComplete case analysisConsistent estimatesRobust approachInverse probability weightingBiased estimatesMissingnessOutcome distributionModeling approachProbability weightingData processSensitivity analysisOutcome modelModelEstimatesBrief discussionPractical considerationsInferenceApproachImputation
2016
PhyloOncology: Understanding cancer through phylogenetic analysis
Somarelli JA, Ware KE, Kostadinov R, Robinson JM, Amri H, Abu-Asab M, Fourie N, Diogo R, Swofford D, Townsend JP. PhyloOncology: Understanding cancer through phylogenetic analysis. Biochimica Et Biophysica Acta (BBA) - Reviews On Cancer 2016, 1867: 101-108. PMID: 27810337, PMCID: PMC9583457, DOI: 10.1016/j.bbcan.2016.10.006.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsAdaptation, PhysiologicalAlgorithmsAnimalsBiomarkers, TumorCell Transformation, NeoplasticEvolution, MolecularGene Expression Regulation, NeoplasticGenetic FitnessGenetic Predisposition to DiseaseGenomicsHeredityHumansModels, GeneticMutationNeoplasmsPedigreePhenotypePhylogenySignal TransductionSystems BiologyTime FactorsConceptsDr. Robert A. GatenbyGenome-scale dataSystems biology approachPowerful systems biology approachUse of phylogeneticsPhylogenetic analysisBiology approachPhylogenetic applicationsSubclonal evolutionCancer biologyCancer progressionSuite of algorithmsPhylogeneticsCancer data setsCancer samplesImproved therapeutic interventionRobust approachDecades of researchFundamental insightsNew toolBiologyDiverse fieldsGatenbyData setsTherapeutic interventions
2000
Physical model-based non-rigid registration incorporating statistical shape information
Wang Y, Staib L. Physical model-based non-rigid registration incorporating statistical shape information. Medical Image Analysis 2000, 4: 7-20. PMID: 10972317, DOI: 10.1016/s1361-8415(00)00004-9.Peer-Reviewed Original ResearchConceptsStatistical shape informationStatistical shape modelDeformable elastic solidsComplex anatomical detailsIntensity similarity measureShape modelBayesian formulationBoundary shape informationViscous fluidCorresponding boundary pointsElastic solidsBoundary pointsDense setPhysical modelRobust approachSparse setReal medical imagesNumber of experimentsFirst methodShape informationSimilarity measureSetPhysical propertiesModelSmoothness
1998
Integrated approaches to non-rigid registration in medical images
Wang Y, Staib L. Integrated approaches to non-rigid registration in medical images. 1998, 102-108. DOI: 10.1109/acv.1998.732865.Peer-Reviewed Original ResearchIntensity similarity measureNon-rigid registrationSimilarity measureMedical imagesShape informationStatistical shape modelReal medical imagesShape modelStatistical shape informationBoundary shape informationComplex anatomical detailsTraining setBayesian formulationDeformable elastic solidsBoundary pointsAtlas-based methodRobust approachDense setInformationRegistrationImagesPhysical modelElastic solidsImproved physical modelViscous fluid
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