vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff55572b000000c3ca000001000d00
Deep learning is a subdivision of machine learning that employs computation models made of several layers to learn features from data with different levels of abstraction. Implementation of these models has led to a startling improvement in areas such as visual object recognition, drug discovery, and genomics. This paper presents a deep learning algorithm, based on a convolution neural network to classify brain MRI into five classes. The designed model achieves a test accuracy of 97.5% demonstrating the potential of deep learning in automated disease diagnosis. A standalone application has also been developed to display the classifier output and activations of convolution and ReLu layers.