Predicting breast cancer treatment response and prognosis using AI-based image classification

By learning temporal dynamics in a personalized manner, the proposed model enhances predictive performance while remaining sensitive to patient-specific variations and therapeutic regimens. Through extensive validation on real-world breast cancer cohorts, we demonstrate that our framework not only outperforms existing baselines but also provides actionable insights that can inform adaptive treatment planning and risk stratification.