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B0640
Title: SILFM: Single index latent factor model based on high-dimensional features Authors:  Hongtu Zhu - University of Texas MD Anderson Cancer Center (United States) [presenting]
Abstract: The aim is to develop a single-index latent factor modeling (SILFM) framework to build an accurate prediction model for clinical outcomes based on a massive number of features. We develop a three-stage estimation procedure to build the prediction model. SILFM uses an independent screening method to select a set of informative features, which may have a complex nonlinear relationship with outcome variables.