Normalize - Standardize - Correlate - Interpret
The SYMEDICAL Server approach is driven by the application of its processing Engines through API requests or integrated service calls.
The Cognition Engine is designed to understand a terminology-domain based upon known phrase patterns, dominant primary and secondary characteristics and other relevant attributes. Terms passed through the Cognition Engine are deconstructed and normalized into specific domain characteristic models, allowing SYMEDICAL Server to “understand” and persist each term’s meaning.
Once
SYMEDICAL Server persists a term in its normalized state, the Coordination Engine is able to correlate its characteristics and attributes to those of another vocabulary set in order to find appropriate matches. The resulting automated or human assisted mapping standardizes the term to the requested standard vocabulary.
Using the persisted representation of terms or the processing of existing relationship models, the RelationSense Engine identifies patterns and infers connections in order to define relationships between concepts. This correlation of concepts across terminology domains makes it easy to create small purpose specific content models that can be reused as components to build larger ontology structures if the need arises.
Sift Engine
Using SYMEDICAL Server’s ability to understand terminology domains, the Sift Engine scans unstructured text looking for the characteristics it recognizes. Once founds, these characteristics are interpreted with other available attributes to interpret and return usable, structured data.
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YMEDICAL Server's Advanced Capabilities