Abstract

Artificial intelligence (AI) has emerged as a transformative force in breast cancer management, offering unprecedented capabilities in predictive modeling and treatment optimization. This abstract provides an overview of recent advancements in AI-driven approaches for breast cancer care. AI-based predictive modeling leverages diverse datasets to accurately assess disease prognosis, recurrence risk, and treatment outcomes, enabling personalized decision-making. Early detection efforts are augmented by AI-powered imaging technologies, enhancing diagnostic accuracy and expediting patient care pathways. Treatment optimization is facilitated by AI-driven decision support systems, which analyze patient-specific data to tailor treatment regimens and predict individual responses to therapy. Moreover, AI holds promise in revolutionizing clinical trial design and drug development, accelerating the discovery of novel therapeutics. Despite the promising advancements, challenges such as data privacy, algorithmic biases, and regulatory considerations must be addressed to realize the full potential of AI in breast cancer management. Embracing AI-driven innovations promises to improve patient outcomes, enhance treatment efficacy, and advance the field of breast cancer research.