Challenges to the Early Diagnosis of Breast Cancer: Current Scenario and the Challenges Ahead

Breast cancer is still a major problem for medical research, science, and society. Breast cancer is the most common form of cancer among women and has a high rate of mortality. Early detection will lessen its impact and could urge victims to receive immediate medical treatment, which will significantly improve the prognosis and likelihood of recovery. However, early detection models suffer from many constraints, like a high-dimensional feature set, imbalanced data, the integration of different data, and generalization. All these constraints make early detection models a challenge. In this review article, we point out the breast cancer detection model’s open research issues. Also, highlight the conventional framework using machine and deep learning along with the method of feature selection, evaluate the conventional model based on accuracy, and concluded with a possible future research direction for breast cancer detection or classification.