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An Ischemic Heart Disease Prediction Model Based on Observed Symptoms Using Machine Learning

Solomon Osarumwense Alile, , , ,
Affiliations
Department of Computer Science, Faculty of Physical Sciences, University of Benin, Benin City, Nigeria
:10.22362/ijcert/2020/v7/i09/v7i0902


Abstract
Ischemic Heart Disease is a death-defying cardiovascular disease that disrupts the circulation of blood owing to plaques such as fats, cholesterol, calcium, and other substances resident in the blood, which coagulates hence narrowing the arteries. The symptoms of this disease are angina, sweating, nausea, breathlessness, heart attack, vomiting, pains of back, jaw, shoulder, arm, back, and neck, just to name but a couple. According to World Health Organization, the leading cause of death which has caused over 17 million untimely deaths of patients since 2015 to date especially individuals below the age of 70 years is Ischemic Heart disease which is a form of Cardiovascular Disease; where 81% of these recorded deaths occurring in individuals in respective of sex, particularly in low and middle-income countries of Sub-Sahara Africa. Nevertheless, in the recent past, a couple of systems have been developed to detect this non-transmittable ailment. Yet, they delivered a ton of bogus negative during testing and could not distinguish Ischemic Heart Disease given its covering symptoms it imparts to other Cardiovascular Diseases. Consequently, there was the need to proffer a solution for the issue of under-diagnosis and misdiagnosis of Ischemic Heart Disease, which is much uncontrolled in Sub-Sahara Africa. Hence, in this paper, we proposed and built up a model to predict Ischemic Heart Disease and Cardiovascular diseases using an AI technique called Bayesian Belief Network. The model was structured using Bayes Server and tested with data retrieved from the UCI Machine Learning Repository. The model had an overall prediction exactness of 99.99%; 98.86% and 99.66% sensitivity of Ischemic Heart Disease and Cardiovascular Diseases correspondingly.


Citation
Solomon Osarumwense Alile."An Ischemic Heart Disease Prediction Model Based on Observed Symptoms Using Machine Learning ". International Journal of Computer Engineering In Research Trends (IJCERT), ISSN:2349-7084, Vol.7, Issue 9,pp.9-22, September - 2020, URL:https://ijcert.org/ems/ijcert_papers/V7I902.pdf,


Keywords : Ischemic Heart Disease, Cardiovascular Diseases, Detection, Prediction, Machine Learning, Supervised Machine Learning, Bayesian Belief Network

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DOI Link : https://doi.org/10.22362/ijcert/2020/v7/i09/v7i0902

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