A comparative analysis of methods for predicting clinical outcomes using high-dimensional genomic datasets.
The objective of this investigation is to evaluate binary prediction methods for predicting disease status using high-dimensional genomic data. The central hypothesis is that the Bayesian network (BN)-based method called efficient Bayesian multivariate classifier (EBMC) will do well at this task because EBMC builds on BN-based methods that have performed well at learning epistatic interactions.
Author(s): Jiang, Xia, Cai, Binghuang, Xue, Diyang, Lu, Xinghua, Cooper, Gregory F, Neapolitan, Richard E
DOI: 10.1136/amiajnl-2013-002358