Artificial intelligence (AI) importance is increasing in advancing personalized medicine, especially in oncology. This research introduces an AI-based therapeutic recommendation system especially designed for breast cancer patients, integrating not only biological and clinical data but also psychological and behavioral factors. The system is designed to enhance treatment adherence and improve patient results by fulfilling individual needs holistically. Recent studies, the system's algorithm is demonstrated in managing complex scenarios, such as co-morbid conditions and psychological challenges that affect therapy adherence. These examples highlight data-driven, patient-centric solutions that closed the gap between technology innovation and human-centered care. While the system offers significant advantages, challenges such as data integration, ethical considerations, and healthcare disparities are discussed. While the system offers spectacular advantages, challenges such as data integration, moral considerations, and healthcare discussed. This study highlights the importance of fostering multidisciplinary collaboration implementation strategies to make sure fair access to AI-driven healthcare solutions. The findings confirmed the transformation impact of integration AI into accurate medicine, paving the way for innovation, efficient, and empathetic healthcare practices especially designed to each patient.

Machine Learning; Artificial Intelligence in Oncology; Digital Transformation in Healthcare; Psychological and Behavioral Factors; medical image processing.