Representation of Medical Concepts of the Thyroid Gland by Physicians in Anatomy and Pathology

L. Pellegrin; C. Bastien; M. Roux

doi:10.1055/s-0038-1635045

Methods of Information in Medicine, Inhaltsverzeichnis

Methods Inf Med 1994; 33(04): 382-389
DOI: 10.1055/s-0038-1635045

Original Article

Schattauer GmbH

Representation of Medical Concepts of the Thyroid Gland by Physicians in Anatomy and Pathology

L. Pellegrin

²Centre de Recherche en Psychologie Cognitive,U.F.R. de Psychologie et Sciences de l’Education, Université Aix-Marseille I, Aix-en-Provence, France

,

C. Bastien

²Centre de Recherche en Psychologie Cognitive,U.F.R. de Psychologie et Sciences de l’Education, Université Aix-Marseille I, Aix-en-Provence, France

,

M. Roux

¹Laboratoire de Biomathématique, Statistique et Informatique Médicale, Faculté de Médecine de Marseille, Université Aix-Marseille II, Marseille, France

› Institutsangaben

Abstract

Abstract:

An experimental study in cognitive psychology is described, concerning the categorization of medical concepts into specific classes, expressed by physicians specialized in anatomic pathology consultations of the thyroid gland. This study belongs to a medical computer science project, called ARISTOTLE, concerning Natural Language Processing of specialized medical reports in anatomic pathology of the thyroid gland. This research has been done for two reasons: first, to specify the characteristics of human expert categorization in an area of medical knowledge and, secondly, to validate the hierarchical organization of a prototype declarative knowledge base. In this experiment, physicians were asked to categorize 121 concepts into 10 proposed classes. These classes and concepts belong to expert knowledge represented in a conceptual graph that was constructed before the experiment. Results show variable semantic distances between concepts of a same class, and dynamic variations of these distances due to contextual representation.

Keywords

Thyroid Gland - Medical Knowledge - Categorization - Context Representation - Semantic Networks

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Referenzen

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