Title: SWRL reasoning on ontology-based clinical dengue knowledge base

Authors: Runumi Devi; Deepti Mehrotra; Hajer Baazaoui Zghal; Ghada Besbes

Addresses: Amity Institute of Information Technology, Amity University Uttar Pradesh, Noida, India ' Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, India ' ETIS UMR8051, ENSEA, CY University, CNRS, F-95000, Cergy, France; Riadi Laboratory, ENSI, Manouba University, Manouba, Tunisia ' Riadi Laboratory, ENSI, Manouba University, Manouba, Tunisia

Abstract: Dengue is a widespread mosquito-borne viral illness that may lead to death if not treated timely and properly. The aim of this study is to propose a semantic rule-based modelling and reasoning approach directed towards formalising dengue disease definition in conjunction with operational definitions (semantics) that support clinical and diagnostic reasoning. The operational definitions are incorporated using Semantic Web Rule Language (SWRL) as logical rules that enhance the expressive capability of the knowledge base. A dengue knowledge base has been designed which is extended with International Classification of Diseases (ICD) ontology for associating dengue fever with ICD code. The knowledge base created can be reasoned upon for diagnostic classification that can discover dengue symptoms and predict the possibility of patients to suffer from the disease apart from offering interoperability. 153 real patient cases are classified successfully against the operational definitions incorporated by SWRL rules.

Keywords: SWRL; ICD-10; DENV; description logic.

DOI: 10.1504/IJMSO.2020.107795

International Journal of Metadata, Semantics and Ontologies, 2020 Vol.14 No.1, pp.39 - 53

Accepted: 17 Jan 2020
Published online: 16 Jun 2020 *

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