Breast cancer, the most prevalent cancer in women worldwide, demands effective screening for early identification and improved treatment outcomes. Recent advances in artificial intelligence (AI) have resulted in dramatic developments in a variety of fields, including healthcare. In this review paper, we look at how AI approaches can be used in breast cancer screening to improve diagnostic accuracy and provide deeper molecular insights. We dig into the complex terrain of breast cancer treatment, which has transformed as a result of the discovery of prognostic and predictive biomarkers, allowing for personalized therapeutic methods based on molecular subgroups. We emphasize the importance of AI-driven approaches in optimizing screening procedures and providing quick and exact findings.

The potential of AI to revolutionize breast cancer screening is highlighted, including its applications in diagnostic imaging, lesion identification, and standardized imaging data interpretation. The analysis highlights AI's critical role in tackling issues associated with the integration of new technologies, providing solutions for worldwide standardization in cancer detection.