A Systematic Review of Breast Cancer Detection Using Machine Learning and Deep Learning
Amit Kumar, Rashmi Saini, Rajeev Kumar
Abstract
Cancer develops when few cells in the body develop abnormally propagate across different regions within the body. Cancer in breast occurs because certain cells in the breast expand unnaturally. These cells keep growing and dividing faster than healthy cells, forming a mass or lump. Most frequently, breast cancer starts with cells in the milk-producing ducts. The clinical treatment of cancer patients may save millions of human lives, depends on early cancer detection and correct treatment plan. There is various research available for identifying cancer in the breast. The efficacy of algorithms based on deep learning and machine learning in predicting cancer of the breast using various data sets is the primary focus of this work. Due to predicting significant feature recognition from extensive breast cancer datasets, machine learning is extensively used for breast cancer pattern classification, nowadays deep learning techniques mostly used in data science for image classification, it offers a revolutionary computer-aided diagnosis method for classifying breast cancer.