An object-oriented design for automated navigation of semantic networks inside a medical data dictionary

Citation
W. Ruan et al., An object-oriented design for automated navigation of semantic networks inside a medical data dictionary, ARTIF INT M, 18(1), 2000, pp. 83-103
Citations number
40
Categorie Soggetti
Research/Laboratory Medicine & Medical Tecnology
Journal title
ARTIFICIAL INTELLIGENCE IN MEDICINE
ISSN journal
09333657 → ACNP
Volume
18
Issue
1
Year of publication
2000
Pages
83 - 103
Database
ISI
SICI code
0933-3657(200001)18:1<83:AODFAN>2.0.ZU;2-A
Abstract
In this paper we present a data dictionary server for the automated navigat ion of information sources. The underlying knowledge is represented within a medical data dictionary. The mapping between medical terms and informatio n sources is based on a semantic network. The key aspect of implementing th e dictionary server is how to represent the semantic network in a way that is easier to navigate and to operate, i.e. how to abstract the semantic net work and to represent it in memory for various operations. This paper descr ibes an object-oriented design based on Java that represents the semantic n etwork in terms of a group of objects. A node and its relationships to its neighbors are encapsulated in one object. Based on such a representation mo del, several operations have been implemented. They comprise the extraction of parts of the semantic network which can be reached from a given node as well as finding all paths between a start node and a predefined destinatio n node. This solution is independent of any given layout of the semantic st ructure. Therefore the module, called Giessen Data Dictionary Server can ac t independent of a specific clinical information system. The dictionary ser ver will be used to present clinical information, e.g. treatment guidelines or drug information sources to the clinician in an appropriate working con text. The server is invoked from clinical documentation applications which contain an infobutton. Automated navigation will guide the user to all the information relevant to her/his topic, which is currently available inside our closed clinical network. (C) 2000 Elsevier Science B.V. All rights rese rved.