AUTOMATIC SNOMED CLASSIFICATION - A CORPUS-BASED METHOD

This paper presents a method of automatic classification of clinical n arrative through text comparison. A diagnosis report can be classified by searching archive texis that show a high textual similarity, and t he 'nearest neighbor' classifies the case. This paper describes the me thod's theoretical background and gives implementation details. Large scale simulation experiments were run with a wide range of histology r eports. Results showed that for 80-84% of the trials, relevant classif ication lines were included among the first five alternatives. In 5% o f the cases, retrieval was unsuccesful due to the absence of relevant archive reports. From the results it is concluded that the method is a versatile approach for finding potentially good classifications. (C) 1997 Elsevier Science Ireland Ltd.