Gene selection using iterative feature elimination random forests for survival outcomes.
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Random Effects Model for Multiple Pathway Analysis with Applications to Type II Diabetes Microarray DataStratified pathway analysis to identify gene sets associated with oral contraceptive use and breast cancer.Statistical aspect of translational and correlative studies in clinical trials.Feature selection through validation and un-censoring of endovascular repair survival data for predicting the risk of re-intervention.RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers.
P2860
Gene selection using iterative feature elimination random forests for survival outcomes.
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2012 nî lūn-bûn
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2012年の論文
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2012年学术文章
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2012年学术文章
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Gene selection using iterative feature elimination random forests for survival outcomes.
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Gene selection using iterative feature elimination random forests for survival outcomes.
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type
label
Gene selection using iterative feature elimination random forests for survival outcomes.
@ast
Gene selection using iterative feature elimination random forests for survival outcomes.
@en
prefLabel
Gene selection using iterative feature elimination random forests for survival outcomes.
@ast
Gene selection using iterative feature elimination random forests for survival outcomes.
@en
P2093
P2860
P356
P1476
Gene selection using iterative feature elimination random forests for survival outcomes
@en
P2093
Herbert Pang
Stephen L George
P2860
P304
P356
10.1109/TCBB.2012.63
P50
P577
2012-09-01T00:00:00Z