Prediction and Classifications of Breast Cancer using Enhanced Convolutional Neural Network Approaches

In worldwide women mortality increases extremely every year due to breast cancer and diagnosis of the issue through prediction is very much imperative for healthy lifespan. Here precision of cancer extrapolation is an essential thing for survivability of patient with appropriate treatment. Deep learning algorithms have materialised as influential tool for predicting breast cancer in medical image processing, which leverages capabilities of artificial neural networks (ANN) that are intended to mimic an architecture and functionalities of human brain. Superior features of convolutional neural network (CNN) in deep learning for handling image-based data like, exploiting spatial information, hierarchical feature learning, parameter sharing and data augmentation are important parameters in medical image processing. In this paper CNN algorithm is incorporated for predicting breast cancer in earlier and malignant stage, the results are compared with other deep learning algorithms and our proposed algorithm is expected to give better performance in parameters like accuracy testing, image classifiers, gene sequence classifiers and malignancy detection.