Browsing by Author "Kayode, A. A."

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    Application of Data Mining Algorithms for Feature Selection and Prediction of Diabetic Retinopathy
    (Computational Science and Its Applications – ICCSA 2019, 2019) Oladele, Tinuke Omolewa; Ogundokun, R. O.; Kayode, A. A.; Adegun, A. A.; Adebiyi, M. O.
    Diabetes Retinopathy is a disease which results from a prolonged case of diabetes mellitus and it is the most common cause of loss of vision in man. Data mining algorithms are used in medical and computer fields to find effective ways of forecasting a particular disease. This research was aimed at determining the effect of using feature selection in predicting Diabetes Retinopathy. The dataset used for this study was gotten from diabetes retinopathy Debrecen dataset from the University of California in a form suitable for mining. Feature selection was executed on diabetes retinopathy data then the Imple mentation of k-Nearest Neighbour, C4.5 decision tree, Multi-layer Perceptron (MLP) and Support Vector Machines was conducted on diabetes retinopathy data with and without feature selection. There was access to the algorithms in terms of accuracy and sensitivity. It is observed from the results that, making use of feature selection on algorithms increases the accuracy as well as the sensitivity of the algorithms considered and it is mostly reflected in the support vector machine algorithm. Making use of feature selection for classification also increases the time taken for the prediction of diabetes retinopathy.
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    An Empirical Investigation of the Prevalence of Osteoarthritis in South West Nigeria: A Population- Based Study
    (International Journal of Online and Biomedical Engineering (iJOE), 2020) Kayode, A. A.; Akande, N. O.; Jabaru, S. O.; Oladele, Tinuke Omolewa
    Today, Osteoarthritis remains the most prevalent chronic joint disease and a potentially incapacitating joint illness. It is an enduring health problem which cannot be cure though it can be managed. Osteoarthritis remains a serious public health problem because its burden is high, people who live with it have a greater risk of developing anxiety / or depression and if it is not properly managed, it can bring about disability as well as impairing quality of life. This paper presents a statistical correlation between the reported risk factors of Osteoarthritis and its prevalence in Nigeria. Statistical tests were performed to investigate if there is enough evidence for inferring that the risk factors for Osteoarthritis are true for the whole of Nigerian population.