Exploring Machine Learning Techniques for Enhanced Breast Cancer Detection

Breast cancer is the second-greatest cause of death for women worldwide, affecting the majority of them. On the other hand, if cancer is identified early and adequately treated, it may be cured. Patients' chances of survival and prognosis can be greatly improved by early identification of breast cancer and prompt treatment intervention. Additionally, accurate benign tumor classification might assist patients in avoiding unnecessary therapy. This study provides a thorough overview of several studies that examined how ML algorithms may be used to find breast cancer. The main goal is to evaluate these algorithms' performance in terms of precision, accuracy, recall, and overall effectiveness. This evaluation tries to identify the most promising approaches and indicate areas for further development by looking at a wide variety of algorithms.