Skip to main content
Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT). Maintained by SNOMED International. The most comprehensive multilingual clinical terminology, covering diagnoses, procedures, findings, and clinical concepts. Used in over 40 countries for electronic health records and clinical documentation. Symphony for SNOMED CT currently outputs three types of SNOMED concept: findings, disorders, and procedures. On the SNOMED CT Entity Linking Challenge it achieves a micro F1 score of 54.8%.
SNOMED CT prediction has been evaluated only on the International edition using American English clinical notes. The model may not perform equally well in other languages or country editions. We encourage you to evaluate it against your own data and use case. If you notice anything that doesn’t look right, please let us know so we can improve it.

​
Filter by attribute

In addition to filtering by code (see Advanced Usage), SNOMED CT concepts can be filtered by semantic_tag, the clinical category a concept belongs to. Combine it with op: "in" to restrict predictions to one or more categories:
Filtering supports the following semantic_tag values:
  • disorder
  • finding
  • procedure
  • regime/therapy

​
Upcoming improvements

This is our first release of SNOMED CT, and we will continuously improve it. We are currently working on the following improvements:
  1. Reducing over-coding of procedures that aren’t clinically relevant to the encounter.
  2. Predicting a negation attribute, so each coded finding or disorder indicates whether it is affirmed or denied. For example, “the patient denies fever” will carry a negation attribute rather than being coded simply as “fever”.
  3. Predicting the subject of each code, so you can distinguish who a condition applies to. For example, “diabetes” will indicate whether it applies to the patient or to a family member.
  4. Predicting temporality, so each code indicates whether a condition is current or historical. For example, distinguishing an active myocardial infarction from a past one.
We have only evaluated this implementation on data from a limited set of specialties. This may not generalize to all hospitals. Contact us to share feedback or report issues.