Support Vector Machine and Deep Learning in Medical Applications

Abstract

Deep learning is a new field in machine learning that focuses mainly on deep neural networks. In this thesis, we focus on machine learning and deep learning, present support vector machine and neural networks, and then we study some medical research in which these methods have been applied. The main deep learning methods in this thesis are convolutional neural networks and recurrent neural networks. After presenting the medical applications we also check some other applications of deep learning. Then we orient to some tools that can be used to implement deep learning algorithms and see how a recurrent neural network could be implemented by using TensorFlow.