A multi-part matching strategy for mapping LOINC with laboratory terminologies.

ABSTRACT:

Objective

To address the problem of mapping local laboratory terminologies to Logical Observation Identifiers Names and Codes (LOINC). To study different ontology matching algorithms and investigate how the probability of term combinations in LOINC helps to increase match quality and reduce manual effort.

Materials and methods

We proposed two matching strategies: full name and multi-part. The multi-part approach also considers the occurrence probability of combined concept parts. It can further recommend possible combinations of concept parts to allow more local terms to be mapped. Three real-world laboratory databases from Taiwanese hospitals were used to validate the proposed strategies with respect to different quality measures and execution run time. A comparison with th

SUBMITTER: Lee LH 

PROVIDER: S-EPMC4147612 | biostudies-literature | 2014 Sep-Oct

REPOSITORIES: biostudies-literature