Accurate Breast Cancer Prediction using Machine Learning Techniques

Abstract

Applications of machine learning (ML) have been increasing widely in various fields like recommendation, fault identification and disease prediction. In ML, different algorithms were available and utilized in disease prediction such as heart disease prediction, cancer prediction and other forms disease prediction. In our proposed work, breast cancer prediction using ML has been implemented. Initially breast cancer images have been taken as input, preprocessing steps will be done to remove noisy and irrelevant data from image. Then 2D median filter is a nonlinear operation often used in image processing to reduce "salt and pepper" noise. To increase contrast of image contrast-limited adaptive histogram equalization is used. Segmentation has been implemented and GLCM feature extraction is deployed based on this information classification is implemented. For accurate classification Artificial neural network (ANN) is used to predict whether the patient is affected by breast cancer or not. Compared to other existing method our method predicts results in accurate way.