title: Using semantic distance for the efficient coding of medical concepts.
abstract: OBJECTIVE
  To use the notion of semantic distance to find the nearest neighbors of a medical concept in a controlled vocabulary.
  
  
  METHODS
  392 concepts from the cardiovascular chapter of the ICD-10 were projected on the axes of SNOMED III. Distances were measured on each axis and the resulting distance was found using a Lp norm.
  
  
  RESULTS
  The distance between a set of ischemic diseases and a set of non-ischemic diseases was significant (p < 0.0001). Our method was validated by finding the k nearest neighbors of ten different diagnoses from the ICD-10 cardiovascular chapter.
  
  
  CONCLUSIONS
  The availability of SNOMED-RT should improve our method. Several more steps are necessary to provide an ideal coding tool.
authors.affiliation: Medical Informatics Department, Broussais Hospital, Paris, France.
authors.forename: C
authors.initials: C
authors.lastname: Bousquet
authors.forename: M C
authors.initials: MC
authors.lastname: Jaulent
authors.forename: G
authors.initials: G
authors.lastname: Chatellier
authors.forename: P
authors.initials: P
authors.lastname: Degoulet
mesh_terms: D002318:Cardiovascular Diseases / Q000145:classification*; D004194:Disease / Q000145:classification; D006801:Humans; D008962:Models, Theoretical; D012660:Semantics; D018875:Vocabulary, Controlled