Determination of Survival-Related Factors in Coronary Artery Disease by Using Machine Learning Algorithms

The aim of this study was to use machine learning methods in determining the factors related to the survival of heart patients in Mashhad. Because survival studies play an important role in medical and health research. Numerous methods have been used in this field and have been published in various magazines. Obviously, each of these methods has its drawbacks. accordingly, much research has been done to find algorithms that can meet the challenges. But so far none of them have been able to overcome all the challenges. In this research, our goal is to introduce algorithms that can overcome the challenges as much as possible and have the appropriate speed and accuracy. So, we first examine the theoretical issues of each method and introduce a series of the most practical machine learning methods in survival analysis. In addition, we will compare the performance of these methods with conventional and classical methods of survival analysis such as the Cox regression method. Then, while presenting the research results, we examine the strengths and weaknesses of each algorithm.