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ABSTRACT
Neglected Tropical Diseases (NTDs) are communicable diseases associated with poverty and prevalent in areas of low-income countries. The NTDs are estimated to affect over one billion people in the world, the majority of who are living in developing countries. In Nigeria, it is estimated that 122 Million persons are at risk of one or more of these NTDs. This is as a result of poor access to medical expert as most of the affected and vulnerable persons lives in rural areas which constitute fewer resource settings. On the other hand, an expert system is systems with the capability of replacing human experts. Its’ discoveries and contributions through Artificial intelligence study since the early 90s has tremendously improved its application in all walks of life. In view of anticipating for people in less recourse settings, the availability of an expert system cannot be overemphasized. Among all of the African nations, Nigeria has the greatest number of people infected with neglected tropical diseases (NTDs). With the right political will, the country has sufficient resources to expand its current investments for the important work of Nigeria's NTD program. In evaluating our methodology, similar work by Yanti et al. (2018) was improved by implementing a web based expert system for the diagnosis of neglected tropical diseases using a rule-based and case-based approach. The expert system was developed using web-based scripting languages PHP, JAVASCRIPT, SQL, AND HTML. The system developed met the study goal which is to diagnose neglected tropical diseases.
