Towards Integrating Data Mining With Knowledge-Based System for Diagnosis of Human Eye Diseases: The Case of an African Hospital

Towards Integrating Data Mining With Knowledge-Based System for Diagnosis of Human Eye Diseases: The Case of an African Hospital

Nilamadhab Mishra, Johny Melese Samuel
Copyright: © 2021 |Pages: 16
DOI: 10.4018/978-1-7998-2742-9.ch024
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Abstract

The eye is the most important sensory organ of vision function. But some eye diseases can lead to vision loss, so it is important to identify and treat eye disease as early as possible. Eye care professionals can help protect their patients from vision loss or blindness by recognizing common eye diseases and recommending for an eye exam. Eye diseases with early detection, treatment, and appropriate follow-up care, vision loss, and blindness from eye disease can be prevented or delayed. In this study, rule-based eye disease identification and advising the knowledge-based system are projected. The projected system is targeting using hidden knowledge extracted by employing the extraction algorithm of data mining. To identify the best prediction model for the diagnosis of eye disease, four experiments for four classification algorithms were performed. Finally, the researchers decided to use the rules of the J48 pruned classification algorithm for further use in the development of a knowledge base of KBS because it exhibited better performance with a 98.5% evaluation result.
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Introduction

Eye problems have been recognized worldwide as one of the major public health problems, particularly in developing countries where 90% of the blind live and international actions to prevent avoidable blindness has been gaining momentum over the last decade. According to the world health organization (WHO), about 37 million people are blind and 124 million people have low vision worldwide [HeMavatHi et al, 2014;World Health Organization, 2006;Aemero et al, 2015;Abdulkerim, 2013]. A large proportion of low vision (91.2%) and blindness (87.4%) are due to avoidable (either preventable or treatable) causes. Females and rural residents carry greater risk for eye problems. The burden of eye disease is believed to pose huge economic and social impacts on individuals, society, and the nation at large [Fayyad et al, 1996, August; Prentzas et al, 2007;Oprea, 2006 ]. A computer-based system (expert system), over-dependence on human experts, can be minimized. Knowledgebase (KBS) benefits the individual by providing a high-quality decision within a given time frame and facilitating job security and personal development [Shiferaw et al, 2015;Berhane et al, 2007; Akerkar et al, 2010]. Also, artificial expertise (AE) has some features that make it more beneficial over human expertise such as permanent, easy to transfer, easy to document, consistent, and affordable [Schreiber et al, 1993; Datta et al, 2011].

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