Distributed Knowledge-based Medical System
For Data Assimilation And Analysis
Author(s)
V. Tomenko & V. Popov
Abstract
Internet and Global Information Systems present unique opportunities to collect,
assimilate and analyse data from different sources. Ontologies allow domain
experts to create, share and reuse existing knowledge in a standardized way.
These advantages can be exploited in medicine in order to create a unified
assimilation and analysis system. An ontology-based server-side application for
distributed medical system was developed. The application uses data from a
medical knowledge base to answer client queries. Additionally, data may be
collected and assimilated into the knowledge base to improve the quality of the
analysis.
Keywords: artificial intelligence, diagnosis, distributed system, knowledge base,
prediction.
1 Introduction
In recent years the development of ontologies has been moving from the realm of
research centres to the desktops of domain experts. Ontologies have become
common on the World-Wide Web. They range from large taxonomies
categorizing Web sites to categorizations of products for sale and their features
(such as on Amazon.com). Many disciplines now develop standardized
ontologies that domain experts can use to share and annotate information in their
fields. Medical experts, for example, have produced standardized, structured
vocabularies such as SNOMED [1] and the semantic network of the Unified
Medical Language System [2].
Ontology can be defined as explicit formal specifications of the terms in the
domain and relations among them [3]. This includes description of classes in the
specific domain (concepts), properties of each class describing various features
Keywords
artificial intelligence, diagnosis, distributed system, knowledge base,
prediction.
Related Book
Other papers in this volume
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