Tichavasia  Alex Dandadzi, Jabulile  Masilela, Ntsoka  Mathiba, Senate  Mafike, Tsakani  Violet Ndobe, Taurai  Hungwe, 
    Optimal Rural Clinic Location Determination using Scientific Modelling,
    Journal of Engineering and Applied Sciences,
    Volume 15,Issue 21,
    2020,
    Pages 3574-3580,
    ISSN 1816-949x,
    jeasci.2020.3574.3580,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2020.3574.3580)
    Abstract: Rural communities are to a larger extent
marginalised resulting in huge populations migrating to
urban areas. This study looked at the poor rural people of
Vezubuhle with their struggle of poor healthcare facilities.
The region has three sections with two clinics situated in
sections with the least population. How that decision on
the two clinics was reached has no scientific basis as
section with the largest population has none. A mixed
research method was followed and scientific modelling
based on statistical and artificial intelligence methods
used. This resulted in an innovative software solution
developed giving optimal results free of bias, corruption,
or favouritism that can be adopted to any other
environment (s) with easy. Authorities in position of
power are therefore, advised to embrace use of
technology, not only does it bring about efficiency, it can
be a huge driving force in attracting investments for the
development of rural areas. There must also be
community involvement if any project affecting its
livelihoodis to be a success.
    Keywords: Rural clinic location;statistical probability of misclassfication;artificial intelligence;technology innovation;optimal scientific modelling;decision making