Breast Cancer Prediction by Ensembling Machine Learning Algorithms and Explainable AI
Mummaneni Sobhana, Anil Kumar Palaketi, Ramya Nalabothu · 2024
A primary cause of death is cancer, which is a result of abnormal cell growth. Globally, breast cancer is a significant contributor to female fatalities, and its prevention is challenging due to unidentified causes. However, early detection is pivotal for reducing risk and improving survival rates. Advanced imaging techniques like mammography and ultrasound are instrumental in diagnosing breast cancer. This model integrates machine learning and Explainable AI to predict breast cancer. Trained on a dataset with diverse features from fine needle aspiration of breast masses, the model not only determines whether a patient is positive or negative but also sheds light on the importance of specific features of the cancerous cell. In cases of a positive diagnosis, early detection empowers patients to promptly seek essential treatment, significantly enhancing their chances of survival.