Ensemble methods for classification of patients for personalized medicine with high-dimensional data
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摘要
ObjectivePersonalized medicine is defined by the use of genomic signatures of patients in a target population for assignment of more effective therapies as well as better diagnosis and earlier interventions that might prevent or delay disease. An objective is to find a novel classification algorithm that can be used for prediction of response to therapy in order to help individualize clinical assignment of treatment.
论文关键词：Class prediction,Cross-validation,Ensembles,Majority voting,Risk profiling
论文评审过程：Received 21 November 2006, Revised 18 June 2007, Accepted 6 July 2007, Available online 23 August 2007.
论文官网地址：https://doi.org/10.1016/j.artmed.2007.07.003
