Broken adaptive ridge method for variable selection in generalized partly linear models with application to the coronary artery disease data. [PDF]
Chan C, Dai X, Chekouo T, Long Q, Lu X.
europepmc +1 more source
Missing data imputation, prediction, and feature selection in diagnosis of vaginal prolapse. [PDF]
Fan M, Peng X, Niu X, Cui T, He Q.
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Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling. [PDF]
Cai K +5 more
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Robust meta gradient learning for high-dimensional data with noisy-label ignorance. [PDF]
Liu B, Lin Y.
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Adaptive CoCoLasso for High-Dimensional Measurement Error Models. [PDF]
Yu Q.
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A powerful penalized multinomial logistic regression approach. [PDF]
Fuetterer C +3 more
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DAGFormer: A graph-based domain adaptation approach for single-cell cancer drug response prediction. [PDF]
Yan F, Du Z, Huang YA.
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HighDimMixedModels.jl: Robust high-dimensional mixed-effects models across omics data. [PDF]
Gorstein E, Aghdam R, SolĂs-Lemus C.
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Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study. [PDF]
Domingo-Relloso A +7 more
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Urinary volatile organic compounds (VOCs) based prostate cancer diagnosis via high-dimensional classification. [PDF]
Quaye GE +5 more
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