New method of judging sub-health state based on rough sets and BP neural network

Bin Liu*, Sen Lin Luo, Li Min Pan, Yun Jie Liu, Ming De Ye, Tie Mei Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

We propose a new decision model for sub-health in this paper. Unlike traditional statistical analysis method, the model is built with rough sets and BP neural network with 18743 items of data owning 155 dimensions of attributes, we divide sub-health state into three different grade at first in order to reflect the precision of the model. The results of experiments show that the precision of judgment is 94.4% for male test data set and 96.53% for female. Besides these, the feedback strategy helps to improve the performance of the model.

Original languageEnglish
Title of host publication2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010
DOIs
Publication statusPublished - 2010
Event2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 - Wuhan, China
Duration: 23 Apr 201025 Apr 2010

Publication series

Name2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010

Conference

Conference2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010
Country/TerritoryChina
CityWuhan
Period23/04/1025/04/10

Keywords

  • BP neural network
  • Bioinformatics
  • Rough sets
  • Sub-health

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