I. Introduction
One of the diseases that has been consistently prevalent in the field of medicine throughout history, and continues to be so, is heart disease (HD) [1]. The occurrence of this disease is attributed to various factors, with the most significant ones being stress, sleepless, high cholesterol diet, sedentary lifestyle, and prolonged periods of sadness, [2]. There are specific types of HD, including arterial hypertension and coronary artery disease (CAD), which the World Health Organization (WHO) has identified as the most common heart ailments [3], [4]. To predict CAD, numerous tests are conducted. However, these tests can be time-consuming and sometimes fail to deliver the desired efficiency, leading to more serious issues for the patients [5]. It is crucial to raise awareness about the risk factors associated with HD and adopt preventive measures to mitigate its impact on individuals and society [6]. A healthy lifestyle, regular exercise, balanced diet, and stress management can significantly reduce the risk of HD development [7]. Moreover, advances in medical technology and research can help improve diagnostic procedures, allowing for earlier detection and better management of heart conditions [8]. The old methods for diagnosing and predicting HD have long been associated with significant time and financial burdens [9]. However, recent research has led to a groundbreaking discovery: the prediction of HD can now be achieved through the use of artificial intelligence techniques [10].