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• W2795859879 abstract "To select genes that are predictive of survival, univariate selection based on the Cox model has been routinely employed in biomedical research. However, this conventional approach relies on the independent censoring assumption, which is often an unrealistic assumption in many biomedical applications. We introduce an alternative approach to selecting genes by utilizing copulas to account for the effect of dependent censoring. We also introduce a method to construct a predictor based on the selected genes to predict patient survival. We use the non-small-cell lung cancer data to demonstrate the copula-based procedure for selecting genes, developing a predictor, and validating the predictor. We provide detailed instructions to implement the proposed statistical methods and to reproduce the real data analyses through the compound.Cox R package." @default.
• W2795859879 created "2018-04-13" @default.
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• W2795859879 date "2018-01-01" @default.
• W2795859879 modified "2023-09-27" @default.
• W2795859879 title "Gene Selection and Survival Prediction Under Dependent Censoring" @default.
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• W2795859879 doi "https://doi.org/10.1007/978-981-10-7164-5_5" @default.
• W2795859879 hasPublicationYear "2018" @default.
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