An Ontology Based Expert System for Lung Cancer : OBESLC
J.Sirisha1, M. Babu Reddy2
1J.Sirisha, Research Scholar, Krishna University, Machilipatnam, Andhra Pradesh, India.
2Dr. M. Babu Reddy, Head(i/c), Department of Computer Science, Krishna University, Machilipatnam, Andhra Pradesh, India.
Manuscript received on November 30, 2019. | Revised Manuscript received on December 02, 2019. | Manuscript published on December 30, 2019. | PP: 4622-4626 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B5116129219/2019©BEIESP | DOI: 10.35940/ijeat.B5116.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Lung Cancer is the second most recurrent cancer in both men and women and which is the leading cause of cancer death worldwide. The American cancer Society (ACS) in US estimates nearly 228,150 new cases of lung cancer and 142,670 deaths from lung cancer for the year 2019. This paper proposes to build an ontology based expert system to diagnose Lung Cancer Disease and to identify the stage of Lung Cancer. Ontology is defined as a specification of conceptualization and describes knowledge about any domain in the form of concepts and relationships among them. It is a framework for representing shareable and reusable knowledge across a domain. The advantage of using ontology for knowledge representation of a particular domain is they are machine readable. We designed a System named OBESLC (Ontology Based Expert System for Lung Cancer) for lung cancer diagnosis, in that to construct an ontology we make use of Ontology Web Language (OWL) and Resource Description Framework (RDF) .The design of this system depends on knowledge about patient’s symptoms and the state of lung nodules to build knowledge base of Lung Cancer Disease. We verified our ontology OBESLC by querying it using SPARQL query language, a popular query language for extracting required information from Semantic web. We validate our ontology by developing reasoning rules using semantic Web Rule Language (SWRL).To provide the user interface, we implemented our approach in java using Jena API and Eclipse Editor.
Keywords: Semantic Web, Ontology, Lung Cancer, RDF, OWL, SWRL, SPARQL.