Deep Learning-Based Brain Tumor Classification Prototype Using Transfer Learning

Accumulation of cells with unimpeded growth is the hallmark for the development of life challenging brain tumor disease. In pre-existing research Machine Learning analytical models are trained on domain specific dataset to achieve goals of an Artificial Intelligence based application in Computer Science for the said disease identification. An ongoing research in the field is presented in this paper where an experimental set of 7038 domain specific images are used to train a model. On experiments conducted on the dataset using six different Machine Learning algorithms the researchers are able to identify Glioma tumor, Meningioma tumors and Pituitary tumor with an accuracy of 96% using RESTNET 5.0 with Transfer Learning Model.