A Study on Mammogram Image Based Breast Cancer Classification and Detection Using Machine Learning Model

Breast cancer is one of the most common malignancies in women; as of 2022, there were about 287,850 new cases identified. 43,250 of them lost their lives to this illness. The mortality rate of this malignancy may be lowered with an early diagnosis. But manually diagnosing this cancer from mammography images is a challenging task that requires an expert in every case. Numerous methods based on artificial intelligence (AI) have been proposed in literature. Nevertheless, they continue to face several difficulties, including inadequate training models, irrelevant feature extraction, and similarities between cancerous and non-cancerous areas. It has been demonstrated that early detection of breast cancer lowers mortality risks by increasing the likelihood of finding effective therapy. Artificial intelligence and machine learning are essential components of healthcare systems because they help doctors diagnose and treat a wide range of illnesses more accurately and quickly. The impacts of several machine learning algorithms for the automated categorization of mammography images are examined in this study. This study compiles agent works that demonstrate the use of machine learning techniques to various problems found through various analytical science tests. This work illustrates the effects of pre-processing mammography images before to input into the classifier, resulting in improved classification accuracy.