APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR PREDICTING HYPERTENSION STATUS AND INDICATORS IN HADEJIA METROPOLITAN
DOI:
https://doi.org/10.33003/fjs-2023-0701-2052Keywords:
Artificial Neural Network, Multilayer Perceptron, Hypertensive Status, Hypertension Related information, Hadejia metropolisAbstract
The responsibilities of hypertension or long blood pressure is rapidly increasing worldwide. Jigawa state in Nigeria seems to be one of the most affected states in the country. The frequency of hypertension in Hadejia forms an ongoing section of the overall responsibility in Jigawa state because of its population among local governments in the state. The purpose of this research is to determine the frequency and classification of a case of hypertension in Hadejia. A survey for some factors was conducted to identify which among the factors impact the prevalence of long blood pressure in Hadejia. It can be seen that the overall prevalence of hypertension in the study was found to be 45.97156% and 54.02844% were found to be non-hypertensive among the categories, those who are married have a higher prevalence of 35.07109%. The study produced the results shown in Table 2, which show the frequency of hypertensive and non-hypertensive patients among the categories and the prevalence of hypertension among those categories. Non-diabetic and those whose parents are hypertensive have the same prevalence of 34.12322% whereas those at or below 25 years of age have a less prevalence of 1.421801% of hypertension. Likewise, in Table 4, ANN with 64.3% of accuracy (sensitivity). The outcome for the testing sample performed better with an accuracy of 64.35% than that for the training sample with an accuracy of 70.4%, and the result shows that Age, Diabetics, and parental Hypertension Status are contributing to the prevalence of Hypertension or long blood pressure.
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