Using semantic distance for the efficient coding of medical concepts.
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.
Bousquet
C
C
Medical Informatics Department, Broussais Hospital, Paris, France.
Jaulent
M C
MC
Chatellier
G
G
Degoulet
P
P
D002318:Cardiovascular Diseases / Q000145:classification*; D004194:Disease / Q000145:classification; D006801:Humans; D008962:Models, Theoretical; D012660:Semantics; D018875:Vocabulary, Controlled