ABSTRACT
Nigeria. a country in the tropics, is not free from tropical diseases. The commonest ones
being malaria, typhoid and tuberculosis. Malaria alone results in over 300,000 deaths every
year. Adding to this, there is a serious shortage of Doctors. A survey by the World Health
Organization has shown that there is approximately I Doctor to about 2,660 Nigerians. Due
to this. the Health sector is stressed beyond its carrying capacity and Doctors cannot
perform at their best. Nigerians are discouraged from going to the hospital because when
they do. they meet with unending queues and angry health personnel. These result in selfmedication,
drug abuse and deaths. Several works have been developed to aid diagnosing
of tropical diseases using fuzzy logic. This work developed an Android-based solution to
shorten patient waiting time.
Artificial Intelligence is being applied in several endeavours including medicine. These
Systems have shown greater accuracy than experts in the fields where they serve. This
performance benefit should also be harnessed for the diagnosis and management of tropical
diseases in Nigeria. This project develops an Android-based expert system for the diagnosis
of some tropical diseases using hybridization of Fuzzy logic and Analytic Hierarch)
Process. At the knowledge acquisition stage, questionnaires were administered to medical
doctors at four hospitals. Fuzzy rules were extracted from the questionnaires using a
method called Learning from Example. The system was designed on MATLAB and
FuzzyTECH software. Subsequently, it was implemented on the Android platform using
Java programming language and XML.
Evaluation was done by comparing the sensitivity and consultation time of the developed
system to that of medical doctors. The system showed 72% sensitivity compared to 62'Yo of
medical doctors and consultation time was reduced by up to 15%. This study has shown
that an Android-based Fuzzy-AHP diagnosis system can help to reduce the stress on the
health sector in Nigeria and other developing countries thereby reducing mortality due to tropical diseases.
JEHOFADUNSIN, A (2021). An Android-Based Expert System For Diagnosis Of Selected Tropical Diseases Using Fuzzy-Analytic Hierarchy Process. Afribary. Retrieved from https://afribary.com/works/an-android-based-expert-system-for-diagnosis-of-selected-tropical-diseases-using-fuzzy-analytic-hierarchy-process
JEHOFADUNSIN, ALEGBELEYE "An Android-Based Expert System For Diagnosis Of Selected Tropical Diseases Using Fuzzy-Analytic Hierarchy Process" Afribary. Afribary, 21 May. 2021, https://afribary.com/works/an-android-based-expert-system-for-diagnosis-of-selected-tropical-diseases-using-fuzzy-analytic-hierarchy-process. Accessed 23 Nov. 2024.
JEHOFADUNSIN, ALEGBELEYE . "An Android-Based Expert System For Diagnosis Of Selected Tropical Diseases Using Fuzzy-Analytic Hierarchy Process". Afribary, Afribary, 21 May. 2021. Web. 23 Nov. 2024. < https://afribary.com/works/an-android-based-expert-system-for-diagnosis-of-selected-tropical-diseases-using-fuzzy-analytic-hierarchy-process >.
JEHOFADUNSIN, ALEGBELEYE . "An Android-Based Expert System For Diagnosis Of Selected Tropical Diseases Using Fuzzy-Analytic Hierarchy Process" Afribary (2021). Accessed November 23, 2024. https://afribary.com/works/an-android-based-expert-system-for-diagnosis-of-selected-tropical-diseases-using-fuzzy-analytic-hierarchy-process