BREAST CANCER RISK PREDICTION AND DIAGNOSIS USING MACHINE LEARNING ALGORITHMS

Breast cancer is a common and deadly condition that affects people all over the world. For patients to have better results, precise risk assessment and early detection are essential. Machine learning algorithms have demonstrated promising outcomes in a number of medical applications, including the detection and risk assessment of breast cancer. This study intends to investigate the potential of machine learning algorithms for risk prediction and accurate detection of breast cancer. We go over the value of risk prediction models, point out the difficulties in diagnosing breast cancer, and give an overview of machine learning methods applied to breast cancer research. Additionally, we give a thorough analysis of current research and developments in this area, outlining the benefits and drawbacks of various machine learning techniques. The results of this study can help medical professionals use machine learning-based methods for better risk assessment and early identification of breast cancer.