Abstract:
In medicine, as in other domains, indexing and classification is a natural human task
which is used for information retrieval and representation. In the medical field,
encoding of patient discharge summaries is still a manual time-consuming task. This
paper describes an automated coding system of patient discharge summaries from the
field of coronary diseases into the ICD-9-CM classification. The system is developed
in the context of the European AIM MENELAS project, a natural-language understanding
system which uses the conceptual-graph formalism. Indexing is performed by using a
two-step processing scheme; a first recognition stage is implemented by a matching
procedure and a secondary selection stage is made according to the coding priorities.
We show the general features of the necessary translation of the classification terms
in the conceptual-graph model, and for the coding rules compliance. An advantage of
the system is to provide an objective evaluation and assessment procedure for natural-language
understanding.
Keywords:
Natural-Language Processing - Conceptual Graphs - Knowledge-Based System - Indexing
- Coronary Diseases - ICD-9-CM