Evolutionary methods for variable selection in the epidemiological modeling of cardiovascular diseases.

ABSTRACT:

Background

The redundancy of information is becoming a critical issue for epidemiologists. High-dimensional datasets require new effective variable selection methods to be developed. This study implements an advanced evolutionary variable selection method which is applied for cardiovascular predictive modeling. The epidemiological follow-up study KIHD (Kuopio Ischemic Heart Disease Risk Factor Study) was used to compare the designed variable selection method based on an evolutionary search with conventional stepwise selection. The sample contains in total 433 predictor variables and a response variable indicating incidents of cardiovascular diseases for 1465 study subjects.

Results

The effectiveness of variable selection methods was investigated in combination with two model

SUBMITTER: Brester C 

PROVIDER: S-EPMC6092817 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature