A complementary graphical method for reducing and analyzing large data sets. Case studies demonstrating thresholds setting and selection.

ABSTRACT:

Objectives

Graphical displays can make data more understandable; however, large graphs can challenge human comprehension. We have previously described a filtering method to provide high-level summary views of large data sets. In this paper we demonstrate our method for setting and selecting thresholds to limit graph size while retaining important information by applying it to large single and paired data sets, taken from patient and bibliographic databases.

Methods

Four case studies are used to illustrate our method. The data are either patient discharge diagnoses (coded using the International Classification of Diseases, Clinical Modifications [ICD9-CM]) or Medline citations (coded using the Medical Subject Headings [MeSH]). We use combinations of different thresholds to ob

SUBMITTER: Jing X 

PROVIDER: S-EPMC4209908 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature