NMFBFS: A NMF-Based Feature Selection Method in Identifying Pivotal Clinical Symptoms of Hepatocellular Carcinoma.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is a highly aggressive malignancy. Traditional Chinese Medicine (TCM), with the characteristics of syndrome differentiation, plays an important role in the comprehensive treatment of HCC. This study aims to develop a nonnegative matrix factorization- (NMF-) based feature selection approach (NMFBFS) to identify potential clinical symptoms for HCC patient stratification.

Methods

The NMFBFS approach consisted of three major steps. Firstly, statistics-based preliminary feature screening was designed to detect and remove irrelevant symptoms. Secondly, NMF was employed to infer redundant symptoms. Based on NMF-derived basis matrix, we defined a novel similarity measurement of intersymptoms. Finally, we converted each group of redundant sym

SUBMITTER: Ji Z 

PROVIDER: S-EPMC4633688 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature