Due to its structure and formalism, this ontology has assured the ability to integrate terminology from different relevant scientific sources and it has enabled semantic interoperability.
This permits to combine the two levels of the dual model-based architecture in one modeling framework which can also integrate terminologies available in OWL format.
In practice, large-scale manual mapping is the most common endeavor, in which teams of consultants (such as Apelon or Intelligent Medical Objects) are employed to integrate terminologies.
For reminder rules, the RAEs are not fully integrated with terminology services and KEs have to manually lookup and transcribe the relevant terminology concepts and classes.
Thus, testing different indexing techniques for coded information integrated with terminology servers needs to be explored.
R. Brachman, R. Fikes, and H. Levesque; KRYPTON: Integrating Terminology and Assertion; Proceedings of the National Conference on Artificial Intelligence; Washington D.C.; 1983.
To work toward this goal, integrated medical/biological terminologies and ontologies have to be adopted, together with advanced semantic-based models and natural language processing (NLP) techniques to objectively describe medical and biomolecular findings.
Rule authoring environment (RAE) refers to the suite of tools that manage the end-to-end process of creating specifications for rules, integrating with terminology, and authoring, testing, publishing and reporting on those rules.
These databases are cross-referenced between each other, providing a way to collect and integrate the terminology for a specific gene/protein entity from the different sources in a single entity.
RAEs include not only rule editors used to author rules, but also other ancillary tools needed to span the steps of the rule authoring process as described in Figure 1: creating knowledge specifications, integrating with terminology, authoring rules, testing rules, publishing rules and reporting.
