Abstract: To eliminate some of the inaccuracies in the diagnosis of human diseases, decision support systems based on algorithms and technologies such as Artificial Neural Network, Fuzzy Logic etc. have been used. The results of such diagnosis are used for treatment and management purposes. Inaccurate and imprecise diagnosis may lead to wrong treatment methods which in turn may result in death or complications. Although treatments are widely carried out using drugs, there exist other treatment methods such as alternative medicine, complimentary medicine which could be used for treatment. We propose an Integrated Fuzzy Based Decision Support System which focuses on the integration of both alternative and pure medicine for the management of malaria. The results obtained showed that integrating these two treatment and management methods will eliminate the limitations of the individual methods therefore bridging the gap between alternative and pure medicine in the treatment and management of human diseases. The system is implemented in C#.

Blessing Ekong, Idara Ifiok, Ifreke Udoeka and James Anamfiok, “Integrated Fuzzy based Decision Support System for the Management of Human Disease” International Journal of Advanced Computer Science and Applications(IJACSA), 11(2), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110235

@article{Ekong2020,
title = {Integrated Fuzzy based Decision Support System for the Management of Human Disease},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110235},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110235},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {2},
author = {Blessing Ekong and Idara Ifiok and Ifreke Udoeka and James Anamfiok}
}