Self-evolving disease ontology for medical domain based on web

Abstract

In last decade information technology has gained a rapid development, and today it plays a crucial role in everyone's life. It makes the life more comfortable for professional to do their work. Every performance and the innovating task will become more comfortable if there is a proper and accurate knowledge base containing up to date information. It will be an added advantage if the so-called knowledge base could shrink and expand dynamically. Especially in the medical domain, there is a higher demand and necessity for such kind of knowledge base which evolves dynamically with time and data because medical field is rapidly evolving and new biomedical entities such as diseases, symptoms, proteins, and so forth are frequently introducing. This study proposes a mechanism to generate dynamically evolving ontology for the biomedical domain which evolves with new relations explores from web data and patient history records. Proposed approach retrieves information from the ontology and generates probabilistic values for each relationship in the disease ontology. This approach used to create a dynamically evolving ontology for the medical domain to manage the relationship between diseases and symptoms more effectively. Furthermore, it retrieves data from the ontology to answer user queries related to the diseases and symptoms.