Clinical research based on data from patient or study data management systems plays an
important role in transferring basic findings into the daily practices of physicians. To support study
recruitment, diagnostic processes, and risk factor evaluation, search queries for such management
systems can be used. Typically, the query syntax as well as the underlying data structure vary
greatly between different data management systems. This makes it difficult for domain experts (e.g.,
clinicians) to build and execute search queries. In this work, the Core Ontology of Phenotypes is used
as a general model for phenotypic knowledge. This knowledge is required to create search queries
that determine and classify individuals (e.g., patients or study participants) whose morphology,
function, behaviour, or biochemical and physiological properties meet specific phenotype classes. A
specific model describing a set of particular phenotype classes is called a Phenotype Specification
Ontology. Such an ontology can be automatically converted to search queries on data management
systems. The methods described have already been used successfully in several projects. Using
ontologies to model phenotypic knowledge on patient or study data management systems is a viable
approach. It allows clinicians to model from a domain perspective without knowing the actual data
structure or query language.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:87378 |
| Date | 10 October 2023 |
| Creators | Beger, Christoph, Matthies, Franz, Schäfermeier, Ralph, Kirsten, Toralf, Herre, Heinrich, Uciteli, Alexandr |
| Publisher | MDPI |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 5214, 10.3390/app12105214 |
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