2024
Parameter optimization for stable clustering using FlowSOM: a case study from CyTOF
Tao W, Sinha A, Raddassi K, Pandit A. Parameter optimization for stable clustering using FlowSOM: a case study from CyTOF. Frontiers In Immunology 2024, 15: 1414400. PMID: 39445014, PMCID: PMC11497637, DOI: 10.3389/fimmu.2024.1414400.Peer-Reviewed Original ResearchParameter optimizationMachine learning methodologyMachine learningComplex dataClustering outcomesLearning methodologyAssociated with immune disordersModified pipelineCell phenotypeImmune cell populationsDatasetBugsAutomated gatingOptimizationMachineImmunological datasetsImmune disordersScalabilityStable clustersCell populationsPipelineCellular changesCase studyCyTOFCyTOF data
2008
Bayesian Mass Spectra Peak Alignment from Mass Charge Ratios
Liu J, Yu W, Wu B, Zhao H. Bayesian Mass Spectra Peak Alignment from Mass Charge Ratios. Cancer Informatics 2008, 6: 117693510800600006. DOI: 10.4137/117693510800600006.Peer-Reviewed Original Research
2007
Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality
Matheny M, Resnic F, Arora N, Ohno-Machado L. Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality. Journal Of Biomedical Informatics 2007, 40: 688-697. PMID: 17600771, PMCID: PMC2170520, DOI: 10.1016/j.jbi.2007.05.008.Peer-Reviewed Original ResearchConceptsSupport vector machineRadial Basis Kernel Support Vector MachineKernel support vector machineCross-entropy errorSVM parameter optimizationUnseen test dataSVM kernel typesTraining dataVector machineEvolutionary algorithmGrid searchMean squared errorKernel typeMachineOptimization methodPrediction modelNumber of methodsParameter optimizationTest dataMedical applicationsOptimization parametersMortality prediction modelAlgorithmBest modelApplications
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