Australian e-Health Research Centre
Australian e-Health Research Centre Australian e-Health Research Centre

Snorocket : Ontology Classification Engine

Snorocket is an implementation of the Dresden algorithm that is tuned for classifying the SNOMED CT clinical terminology. As the name suggests, Snorocket is fast, able to classify SNOMED CT at least an order of magnitude faster than other known classifiers. Snorocket underpins the development of other solutions at AEHRC which use the SNOMED CT terminology for integrating, querying or retrieving health and health related data. Snorocket provides a simple API for supporting third party tools with the need for fast classification of large ontologies.

A number of extensions for SNOMED CT are now being developed by standards bodies world wide. The development and use of specific extensions, for particular diseases or domains (e.g., pharmaceuticals) will require tools, such as Snorocket, which can process these complex knowledge bases. Below is an image of a small part of the SNOMED CT ontology with ICD 10 codes added as a specific extension. Snorocket is able to process the complete extended ontology in under a minute.

For more information about SNOMED CT see the SNOMED CT project page.