Application of multilayer perceptron neural networks and support vector machines in classification of healthcare data

A large volume of data is steadily produced by the healthcare industry on daily basis. Data mining and machine learning approaches are two effective techniques applicable for data analysis and finding the hidden patterns which can be utilized for medical decision making. As the decisions in medical field are dealing with patient outcome, a high level of accuracy in data mining is needed. In this paper a comparison between implemented multilayer perceptron neural networks and support vector machine on heart diseases dataset is conducted. We have analyzed the effectiveness of support vector machine in classification, using a dataset of 303 patients. Our results show that support vector machine is able to classify more accurately.