Modeling of Post-Myocardial Infarction and Its Solution Through Artificial Neural Network

Dr. Noor Badshah Naheed Ali
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Dr. Noor Badshah Naheed Ali: Dept. of BasicSciences and IslamiatUniversity of Engineering and Technology Peshawar, Pakistan

International Journal of Innovations in Science & Technology, 2024, vol. 6, issue 5, 18-29

Abstract: Cardiovascular diseases, particularly myocardial infarction (MI) constitute a significant health concern globally. A myocardial infarction, which is commonly known as a heart attack, happens when a part of the heart muscle doesn’t get enough blood because of a blockage. Studying MI is complex and it requires looking at it from different angles. In recent years the fusion of mathematical modeling and artificial intelligence (AI) techniques has emerged as a promising avenue for understanding the complexities associated with MI. The primary goal of this study is to provide an AI-based solution for a new nonlinear mathematical model related to myocardial infarction phenomena. To obtain the solution we will use a well-known deep learning technique, known as artificial neural networks (ANNs) with the combination of the optimization technique Levenberg-Marquardt back propagation (LMB). This combined method is referred to as ANNs-LMB. The results obtained from the model using ANNs-LMB are compared with a reference dataset constructed through the adaptive MATLAB solver ode45. The numerical performance is validated through a reduction in mean square error (MSE). The MSE is around and the obtained results by ANNs-LMB almost overlapped with the reference dataset, which shows the accuracy and efficiency of the proposed methodology.

Keywords: Artificial Neural Network; Myocardial Infarction; Mathematical Modeling (search for similar items in EconPapers)
Date: 2024
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