Early Detection and Classification of Breast Cancer Using Mammograms by Machine Learning

Machine learning-based classification of breast cancer and its detection is possible without toxic therapy by a well-trained model. The machine learning model detects features and patterns form the data sets that used when training model which is useful for detecting tumor and classify whether it is a benign or malignant and this process simplifies the cancer detection and gives results accurately at a faster rate when compared to the other traditional methods like Magnetic resonance imaging (MRI), Coronary artery disease (CAD), Modalities using ultrasound, etc. Here I am proposing a new technique through which breast cancer can be easily detected by a proper training model with the help of few classifying algorithms in this research a good set of data is used for training classifier machine algorithms in Microsoft azure by comparing all those five algorithms accuracy and working these are the five algorithm models are 2-class Support vector machine, 2-class Neural Networks, 2-class Boosting Tree, 2- Class Logistic Regression, 2-Class Bayes Point and acquired better results which can lead and helpful for detecting cancer in future by using machine learning and deep learning techniques.

Keywords: Benign, Deep Neural Networks, Malignant, Modality, Simple Neural Networks, Tumor.