Artificial intelligence revolution in breast cancer management: a comprehensive review

Abstract

Breast cancer continues to be a leading cause of cancer-related morbidity and mortality among women globally. Existing clinical management strategies are often constrained by limitations in precision, personalization, and operational efficiency. In recent years, artificial intelligence (AI) has emerged as a transformative force in breast oncology, revolutionizing diagnostic accuracy, refining treatment protocols, and enhancing prognostic assessments. By leveraging advanced computational techniques, AI improves the interpretation of ultrasound, radiological and histopathological images, facilitates the development of personalized treatment regimens, and enables more accurate risk stratification through the integration of multi-omics data. A deeper understanding of these AI-driven innovations is crucial for promoting the transition toward a more data-informed and individualized paradigm of breast cancer care. This review provides a comprehensive analysis of the expanding role of AI in breast oncology, highlighting its potential to redefine standards of care and shape the future trajectory of precision oncology.

Keywords

Breast cancer / Artificial intelligence / Machine learning / Deep learning / Medical imaging / Multi-omics / Clinical translation / Decision support system / Precision oncology / Drug discovery

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