According to this paper, we can kno

According to this paper, we can know that Cardiovascular diseases (CADs) are the first leading cause of death across the world. So there are two data mining algorithms to predict coronary artery disease. Therefore, this study was designed to compare the use of artificial neural networks (ANN) and SVM algorithm and its positive predictive value in terms of choice of hospital predicting CAD difference of (PPV). Although there are lots of ways to predict the diseases, People think less of compare them. So purpose of the paper is to compare the two typical algorithms. (could you present these two method after your special knowledge?)This paper use the methods SVM and PPV.I know the two methods K-means algorithm and Naive Bayes.The results show that the neural network model can fit these data well, and the total PPV is 0.798. On the other hand, support vector machine algorithm has smaller mapping error and error for data fitting. The larger the goodness of fit test value of hosmer-leme show is, the better the SVM model is in data, which provides a better prediction for CAD diagnosis. In addition, the PPV and sensitivity of SVM are higher than that of ANN. Similarly, previous studies have shown that SVM can predict disease and distinguish patients from non patients with higher accuracy.The study also confirmed the superior performance of SVM and accuracy. However, few studies have confirmed the effectiveness of the algorithm and proposed other methods, such as binary particle swarm optimization (bpso) and genetic algorithms to select the best model as a cad determined [64]. Although the choice of input variables based on the literature review and guidelines, but there may be other risk factors can be studied in the future, a more comprehensive understanding of risk factors for disease. In addition, the article also compares the results of the two algorithms. Data can be used to test other algorithms, such as genetic algorithm to identify the best model performance. Conclusions medical condition prediction process is an important decision-making process, doctors need to understand the risk factors for different diseases. And methods by using a logical object, such as machine learning and data mining algorithms, this process can be simplified. Currently, due to the large increase in heavy economic burden of cardiovascular disease and to society, health care community is seeking to predict, methods of diagnosis and treatment of these diseases. The results show that, using data mining algorithms, such as the SVM model can predict cad. However, it is necessary to compare the performance of different algorithms more research and find out the best performance models.