Joint modeling of mixed outcomes using a rank-based sparse neural network
Xue J, Xu Y, Li J, Ma S, Fang K. Joint modeling of mixed outcomes using a rank-based sparse neural network. Journal Of Biomedical Informatics 2025, 169: 104870. PMID: 40623577, PMCID: PMC12306493, DOI: 10.1016/j.jbi.2025.104870.Peer-Reviewed Original ResearchSparse neural networksNeural networkCompetitive performanceImbalance issueLoss functionSparse layerLeverage informationPrediction accuracyTraditional methodsNetworkParametric frameworkPenalization methodFaces challengesJoint modelPrediction modelInformationSkin cutaneous melanomaHigh-throughput profilingHigh-dimensional covariatesDimensionalityGenomic researchFeaturesMethodSimulation studyBiomedical studiesHierarchical Multi‐Label Classification With Gene‐Environment Interactions in Disease Modeling
Li J, Zhang Q, Ma S, Fang K, Xu Y. Hierarchical Multi‐Label Classification With Gene‐Environment Interactions in Disease Modeling. Statistics In Medicine 2025, 44: e10330. PMID: 39865593, PMCID: PMC12201914, DOI: 10.1002/sim.10330.Peer-Reviewed Original ResearchConceptsHierarchical multi-label classificationMulti-label classificationGene-environment interaction analysisGene-environmentEfficient expectation-maximizationGene-environment interactionsSemi-supervised scenariosCancer Genome AtlasUnlabeled dataInteraction analysisExpectation-maximizationGenome AtlasSuperior performanceHierarchical responseDisease outcomeClassificationPenalized estimatorsPractice settingsDisease modelsBiomedical studiesAnalysis literatureE effects
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