Distributed Knowledge-based Medical System For Data Assimilation And Analysis
Free (open access)
V. Tomenko & V. Popov
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  and the semantic network of the Unified Medical Language System . Ontology can be defined as explicit formal specifications of the terms in the domain and relations among them . This includes description of classes in the specific domain (concepts), properties of each class describing various features
artificial intelligence, diagnosis, distributed system, knowledge base, prediction.