Presenting a prediction algorithm for heart patients using data mining

Heart disease is one of the most common human health issues in the world, which there is not a definite method to predict it. The only hopeful way for these patients to continue living is through proper care. The accurate prediction of a patient's heart condition is very critical to prevent any side effects caused by disease. Therefore, in this article, a new method based on a combination of the random forest algorithm used to predict the condition of the patient's heart. The proposed structure can calculate the output corresponding to each learning pattern obtained from performing various experiments on several experimental items and compare them with the desired output of each pattern. For evaluation, the standard UCI data is used. The results show that the obtained accuracy of our method outputs in comparison to similar algorithms is up to 93.3%, which indicates the suitability of the proposed algorithm.