Carcinoma Detection using Convolution Neural Networks

In this paper, we have proposed an optimized model which can predict the symptoms of breast cancer with an accuracy of 86%. The machine learned to predict test images at a more accurate rate than it could without optimization. Using Random forest, we got an accuracy of 83%. We have used Convolutional Neural Network to develop a model for breast cancer detection through a mammograph dataset. With the rapid development in deep learning, in the future, machine learning will surely bring much improvement in development of models for prediction, detection of several health issues even at an early stage and easier procedure. We have used Python language for the implementation of entire system.