Back to search

Article

Cohort Identification Using Semantic Web Technologies: Triplestores as Engines for Complex Computable Phenotyping

2021-12-05

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Computable phenotypes are increasingly important tools for patient cohort identification. As part of a study of risk of chronic opioid use after surgery, we used a Resource Description Framework (RDF) triplestore as our computable phenotyping platform, hypothesizing that the unique affordances of triplestores may aid in making complex computable phenotypes more interoperable a...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
696f06dd-2202-5495-b09d-7b347064f804
DOI
10.1101/2021.12.02.21267186
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Cohort Identification Using Semantic Web Technologies: Triplestores as Engines for Complex Computable PhenotypingDOI 10.1101/2021.12.02.21267186
Select a neighboring publication to make it the new centre.