Methods Inf Med 1992; 31(02): 117-125
DOI: 10.1055/s-0038-1634865
Original Article
Schattauer GmbH

Natural Language Processing and Semantical Representation of Medical Texts

R. H. Baud
1   Centre d’lnformatique Hospitaliere, University State Hospital of Geneva, Geneva, Switzerland
A.-M. Rassinoux
1   Centre d’lnformatique Hospitaliere, University State Hospital of Geneva, Geneva, Switzerland
J.-R. Scherrer
1   Centre d’lnformatique Hospitaliere, University State Hospital of Geneva, Geneva, Switzerland
› Author Affiliations
Further Information

Publication History

Publication Date:
08 February 2018 (online)


For medical records, the challenge for the present decade is Natural Language Processing (NLP) of texts, and the construction of an adequate Knowledge Representation. This article describes the components of an NLP system, which is currently being developed in the Geneva Hospital, and within the European Community’s AIM programme. They are: a Natural Language Analyser, a Conceptual Graphs Builder, a Data Base Storage component, a Query Processor, a Natural Language Generator and, in addition, a Translator, a Diagnosis Encoding System and a Literature Indexing System. Taking advantage of a closed domain of knowledge, defined around a medical specialty, a method called proximity processing has been developed. In this situation no parser of the initial text is needed, and the system is based on semantical information of near words in sentences. The benefits are: easy implementation, portability between languages, robustness towards badly-formed sentences, and a sound representation using conceptual graphs.


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