Classifying ear disorders using support vector machines

One of the most significant causes of iatrogenic injury, death and costs in hospitals is medication errors. A medical decision-support system can help physicians to improve the safety, quality and efficiency of healthcare. In this paper we focus on development of a decision-support system for diagnosis of ear disorders. For this purpose, a dataset obtained from an otolaryngology clinic. Then two machine learning algorithms, Multi-layer perceptron neural network and support vector machine, were applied to classify ear disorders. The results show that support vector machine is considerably more accurate technique for classifying high dimensional data.