Extending import detection algorithms for concept import from two to three biomedical terminologies.

ABSTRACT:

Background

While enrichment of terminologies can be achieved in different ways, filling gaps in the IS-A hierarchy backbone of a terminology appears especially promising. To avoid difficult manual inspection, we started a research program in 2014, investigating terminology densities, where the comparison of terminologies leads to the algorithmic discovery of potentially missing concepts in a target terminology. While candidate concepts have to be approved for import by an expert, the human effort is greatly reduced by algorithmic generation of candidates. In previous studies, a single source terminology was used with one target terminology.

Methods

In this paper, we are extending the algorithmic detection of "candidate concepts for import" from one source terminology to two

SUBMITTER: Keloth VK 

PROVIDER: S-EPMC7737255 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature