Abstract
Today medical ontologies have an important role in medicine field to represent medical knowledge. They are much stronger than biomedical vocabularies. In diseases diagnosis process, each disease has number of symptoms associated with it. We can employ ontology in helping to diagnose diseases by building Diseases-Symptoms ontology, which relate diseases and symptoms. Such ontology would be very useful for medical expert systems to assist physicians in diagnosis diseases or as a training tool for medical students. In this paper, we propose a method that automatically extract medical knowledge from Web resources and build Diseases-Symptoms ontology. We use the linguistic pattern and statistical analysis techniques based on Bing search engine. We evaluated the proposed method for two diseases Hyperthyroidism and Eczema by two consultant physicians.
Highlights
Ontologies consider as fundamental tool to represent knowledge
Automated ontologies construction allows saving time and effort required by knowledge engineers and domain experts to construct specific domain ontology
Medical ontologies have an important role in medicine field
Summary
Ontologies consider as fundamental tool to represent knowledge. They consist of three main elements: classes (domain’s concepts), relations (binary association between classes) and instances (individuals). Ontologies construction carried out by knowledge engineers and domain experts which take long time and effort. This manual approach is always described as bottleneck [2]. Authors [4] state that the relevance of information can measured by the amount of reputations between information Web proved that it is a valid source for knowledge acquisition for many researchers in many areas include questions classification, questions answering and ontology enrichment [5]
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