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The SNOMED CT concept model can also be used to identify potential connections between words and possible postcoordination opportunities. For example, if a term such as 'open fracture' (which is found to be a
| Scg expression |
|---|
404684003|Clinical finding| |
) occurs in close proximity to the term 'femur' (which is found to be an
| Scg expression |
|---|
91723000 | Anatomical structure | |
), then this may indicate that there is a 'finding site' relationship between the concepts. By capturing the concept model rules in a machine-processable way, the SNOMED CT MRCM can be used to assist a range of NLP-supported tasks, including:
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Value set bindings that correspond to a particular concept model attribute (e.g.
| Scg expression |
|---|
272741003 | Laterality | |
) can be designed to be consistent with the appropriate attribute range (e.g.
| Scg expression |
|---|
< 182353008 | Side | |
) defined in the MRCM. Similarly, the MRCM can be used to suggest possible model meaning bindings for an information model, to suggest new data elements that could be added (at either design time or runtime) to represent relevant attribute refinements, and to test existing model meaning bindings for consistency with the concept model.
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