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Construction of Liver Fibrosis Diagnosis Ontology From Fuzzy Extended ER Modeling: Construction of FibrOnto From an EER Model

Construction of Liver Fibrosis Diagnosis Ontology From Fuzzy Extended ER Modeling: Construction of FibrOnto From an EER Model
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Author(s): Sara Sweidan (Mansoura University, Mansoura, Egypt), Hazem El-Bakry (Mansoura University, Mansoura, Egypt) and Sahar F. Sabbeh (University of jeddah, Jeddah, Saudi Arabia)
Copyright: 2020
Volume: 12
Issue: 1
Pages: 24
Source title: International Journal of Decision Support System Technology (IJDSST)
Editor(s)-in-Chief: Pascale Zaraté (Toulouse University, France)
DOI: 10.4018/IJDSST.2020010103

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Abstract

Liver fibrosis diagnoses is a critical and core research study field due to its importance to the patient's life. Moreover, electronic health records (EHR) contain wealthy semantics connected to liver diseases yet ontological implementation is still a challenge. Ontology however, can play critical roles in E-health as a formalization of medical terminologies and decision support system knowledge base. But since clinical data contains a lot of data that is imprecise and vague, classical approaches of ontology construction would not be fruitful. However, Fuzzy ontology, an extension of the crisp ontology that requires different development methodology, can be implemented in this field due to its previous success in modeling semantic knowledge in various domains. In this article, the authors construct a fuzzy ontology by using a fuzzy extended entity relationship (EER) data model for liver fibrosis diagnosis. The resulting ontology is complete and consistent because it is based on a formal methodology of mapping the EER model into a fuzzy ontology.

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