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 will underpin 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 of 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, that can process these complex knowledge bases. Below is an image displaying 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.
Last Updated on Thursday, 29 September 2011 10:43