Author(s)

Kanayo Kizito Uka^1*, Stanley Ikechukwu Oguoma¹, Chekwube Alphonsus Chukwu², Chijioke Izuchukwu Emele¹

¹Department of Computer Science, Imo State University, Owerri, Nigeria.
²Nnamdi Azikiwe Teaching Hospital, Nnewi, Nigeria.

The aim of this paper is to develop an expert system that could aid medical practitioner to effectively diagnose and treat Staphylococcus aureus infections disease on a human. The objective of the research includes to develop an expert system for quick diagnosis and detection of Staphylococcus aureus bacteria on human skin, a system that aids in accurate treatment of staph infectious diseases by doctors, helps in quick decision making in the hospital, improves accuracy in drug prescription, and a system that will bring about computerized storage process, and to enlighten the knowledge workers on how to implement a computer based decision support systems and importance of it in the health care. The research was motivated due to delay in diagnosis and identification of Staphylococcus aureus bacteria and the fast rate at which infectious disease is spreading, delay in treatment of these bacteria, increase of guess work by health practitioners leading to delay in decision making and lack of electronic storage facility in the hospitals. Top down approach was used in the system design of this research while adopting expert system as the methodology and the programming language used was Java and database design used was MySQL. The result after design was a computerized standalone application that assists health practitioners (Doctor’s) in quick identification, diagnosis, prescription and treatment of Staphylococcus aureus bacteria on human skin. The expert system will facilitate quick decision making in the clinic.

Artificial Intelligence, Expert System, Diagnosis, Treatment, Staphylococcus aureus, Infectious Disease

Uka, K.K., Oguoma, S.I., Chukwu, C.A. and Emele, C.I. (2020) Adoption of Artificial Intelligence for Diagnosis and Treatment of Staphylococcus aureus Infections Disease on Humans. E-Health Telecommunication Systems and Networks, 9, 1-15. doi: 10.4236/etsn.2020.91001.