Ensemble methods for classification of patients for personalized medicine with high-dimensional data
Artificial Intelligence in MedicinePublished 24 August 2007
Hojin Moon, Hongshik Ahn, Ralph L. Kodell, Songjoon Baek, Chien-Ju Lin, James J. Chen
Citations97
SJR quartileQ1
SJR score1.40
SNIP1.93
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TL;DR
A robust classification algorithm for high-dimensional data based on ensembles of classifiers built from the optimal number of random partitions of the feature space is developed, expected to play a critical role in developing safer and more effective therapies that replace one-size-fits-all drugs with treatments that focus on specific patient needs.
Abstract
The statistical classification method for individualized treatment of diseases developed in this study is expected to play a critical role in developing safer and more effective therapies that replace one-size-fits-all drugs with treatments that focus on specific patient needs.
Keywords
Biochemistry, Genetics and Molecular Biology
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