Building medical ontologies based on terminology extraction from texts: an experimentation in pneumology.
Pathologies and acts are classified in thesauri to help physicians to code their activity. In practice, the use of thesauri is not sufficient to reduce variability in coding and thesauri do not fit computer processing. We think the automation of the coding task requires a conceptual modelling of medical items: an ontology. Our objective is to help pneumologists code acts and diagnoses with a software that represents medical knowledge by an ontology of the concerned specialty. The main research hypothesis is to apply natural language processing tools to corpora to develop the resources needed to build the ontology. In this paper, our objective is twofold: we have to build the ontology of pneumology and we want to develop a methodology for the knowledge engineer to build various types of medical ontologies based on terminology extraction from texts.
Baneyx
Audrey
A
INSERM U729, Paris, F-75006, France.audrey.baneyx@spim.jussieu.fr
Charlet
Jean
J
Jaulent
Marie-Christine
MC
D006801:Humans; D009323:Natural Language Processing; D015272:Pulmonary Medicine; D012107:Research Design; D012984:Software; D009626:Terminology as Topic; D018875:Vocabulary, Controlled