Ontologies for Liver Diseases Representation: A Systematic Literature Review

Abstract

Ontology, as a useful knowledge engineering technique, has been widely used for reducing ambiguity and helping with information sharing. It is considered originally to be clear, comprehensive and with welldefined format. It characterizes several domains purposes description through structured and formalized languages. In various areas of research, it has become a significant way to realize successful and powerful accomplishments. Actually, medical ontologies were turned into an efficient application in medical domains. They also become a relevant approach to process large medical data volumes. Consequently, they are behaving as a support decision system in some cases. Also, they ensure diagnosis process acceleration and assistance. Additionally, they have been integrated especially to represent human healthcare concepts. For that reason, plenty of research works applied ontologies to design and treat liver diseases. In this article, we present a general overview of medical ontologies to stand for this type of disease. We expose and discuss these works in details by a complete comparison. Also, we show their performance to arrange clinical data and extract results.

A review of data mining ontologies

“…Khamparia and Kaur (2014) performed a comparative study of medical care ontologies based on parameters, like the tools used, representational language, methods and their distinct features. Messaoudi et al (2020) developed a work where they concentrated on reviewing the medical ontologies used for liver disease representation. Okikiola et al (2020) performed a review of the healthcare ontologies to find the information related to the steps, methods, techniques, initiatives and strategies utilized in developing ontologies in the medical domain.…”

Theoretical Perspective of Multi-Dividing Ontology Learning Trick in Two-Sample Setting

“…Hema and Kuppusamy [10] raised a trust-based privacy preservation modelling for service handling by means of ontology service ranking. Messaoudi et al [11] presented a review of medical ontologies. Mantovani et al [12] introduced an ontology based trick for the interpretation and the encoding of the map data.…”