arxivst stuff from arxiv that you should probably bookmark

SAFS: A Deep Feature Selection Approach for Precision Medicine

Abstract · Apr 20, 2017 00:01 ·

stacked risk htn demographic feature hypertension medicine patient personalized lvmi cs-lg stat-ml

Arxiv Abstract

  • Milad Zafar Nezhad
  • Dongxiao Zhu
  • Xiangrui Li
  • Kai Yang
  • Phillip Levy

In this paper, we propose a new deep feature selection method based on deep architecture. Our method uses stacked auto-encoders for feature representation in higher-level abstraction. We developed and applied a novel feature learning approach to a specific precision medicine problem, which focuses on assessing and prioritizing risk factors for hypertension (HTN) in a vulnerable demographic subgroup (African-American). Our approach is to use deep learning to identify significant risk factors affecting left ventricular mass indexed to body surface area (LVMI) as an indicator of heart damage risk. The results show that our feature learning and representation approach leads to better results in comparison with others.

Read the paper (pdf) »