Abstract:

Breast cancer-related tumours can form in breast tissue. It is one of the leading causes of death for women worldwide and the most common type of cancer in females. This article contrasts the detection of breast cancer using data mining, machine learning, and deep learning. However, each technique has a unique accuracy rate that varies based on the circumstances, resources, and datasets used. Many researchers have sought to enhance breast cancer detection and prognosis. Our main objective is to evaluate and contrast the many Machine Learning and Data Mining approaches that are currently in use in order to determine which strategy is the most efficient and will support the massive dataset with the highest prediction accuracy. This article provides all the information a novice needs to comprehend machine learning algorithms and lay a strong foundation for deep learning. The main objective of this study is to highlight all the earlier research on machine-learning algorithms that have been used to detect breast cancer.

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