GE-IA-NAM: gene–environment interaction analysis via imaging-assisted neural additive model
Li J, Xu Y, Ma S, Fang K. GE-IA-NAM: gene–environment interaction analysis via imaging-assisted neural additive model. Bioinformatics 2025, 41: btaf481. PMID: 40880282, PMCID: PMC12452269, DOI: 10.1093/bioinformatics/btaf481.Peer-Reviewed Original ResearchConceptsGene-environmentNeural additive modelsGene-environment modelGene-environment analysisGene-environment interaction analysisEnvironmental factorsCancer Genome AtlasPathological imagesSkin cancer datasetGenome AtlasCancer datasetsNetwork architectureCompetitive performanceGenetic factorsPython codeCancer outcomesInteraction analysisData patternsCancer researchAdditive modelInteraction methodEnvironmental dataJoint analysisCancer modelsRegression-basedBayesian Modeling of Cancer Outcomes Using Genetic Variables Assisted by Pathological Imaging Data
Im Y, Li R, Ma S. Bayesian Modeling of Cancer Outcomes Using Genetic Variables Assisted by Pathological Imaging Data. Statistics In Medicine 2025, 44: e10350. PMID: 39840672, PMCID: PMC11774474, DOI: 10.1002/sim.10350.Peer-Reviewed Original Research
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