Name
Title | ||
|---|---|---|
Using information theory to identify redundancy in common laboratory tests in the intensive care unit |
Abstract | ||
|---|---|---|
Clinical workflow is infused with large quantities of data, particularly in areas with enhanced monitoring such as the Intensive Care Unit (ICU). Information theory can quantify the expected amounts of total and redundant information contained in a given clinical data type, and as such has the potential to inform clinicians on how to manage the vast volumes of data they are required to analyze in their daily practice. The objective of this proof-of-concept study was to quantify the amounts of redundant information associated with common ICU lab tests. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1186/s12911-015-0187-x | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Intensive Care Unit, Mutual Information, Blood Urea Nitrogen, Intensive Care Unit Admission, Redundant Information | Information theory,Data mining,Intensive care unit,Unnecessary Procedure,Computer science,Knowledge management,Data type,Redundancy (engineering),Mutual information,Health informatics,Workflow | Journal |
Volume | Issue | ISSN |
15 | 1 | 1472-6947 |
Citations | PageRank | References |
3 | 0.62 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joon Lee | 1 | 29 | 5.54 |
| David M Maslove | 2 | 14 | 1.86 |