Query-constraint-based mining of association rules for exploratory analysis of clinical datasets in the National Sleep Research Resource.

ABSTRACT:

Background

Association Rule Mining (ARM) has been widely used by biomedical researchers to perform exploratory data analysis and uncover potential relationships among variables in biomedical datasets. However, when biomedical datasets are high-dimensional, performing ARM on such datasets will yield a large number of rules, many of which may be uninteresting. Especially for imbalanced datasets, performing ARM directly would result in uninteresting rules that are dominated by certain variables that capture general characteristics.

Methods

We introduce a query-constraint-based ARM (QARM) approach for exploratory analysis of multiple, diverse clinical datasets in the National Sleep Research Resource (NSRR). QARM enables rule mining on a subset of data items satisfying a query co

SUBMITTER: Abeysinghe R 

PROVIDER: S-EPMC6069291 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature