Integrated Machine Learning and CNN Approaches for Breast Cancer Prediction Using Mammography Images

Abstract

Breast Cancer has increased in the last few years not only in females but also in males, but majorly it affects women’s lives. At the rate at which this issue occurs, we need advanced tools, treatments, and methods to predict breast cancer. Dl and ML are essential parts of AI technology that can be helpful in various domains such as finance, banking, cyber security, and healthcare. With emerging technology, we have various types of data from healthcare settings to test the diseases more robustly, and AI and their related technology are very helpful in analyzing the data and finding out outcomes from patient records to finalize better treatment for it in early stages and to provide a healthy life. DL and ML are widely used for classification problems on imaging data. In this paper, we studied various machine learning models and CNN to find out which model is compatible with medical images to classify them and provide better outcomes. This paper used LR, NB, KNN, Support vector machine, GB, Xtreme gradient boosting, and CNN methods to classify images for malignant and benign images. As for future work, we can study various advanced ensemble learning and deep learning approaches. So that we can predict various types of sensitive medical data more accurately.