Abstract

Artificial intelligence (AI) has emerged as a transformative force in radiology, particularly in the field of palliative oncology imaging. This article explores how AI enhances imaging techniques to support personalized treatment strategies for patients with advanced cancer. By leveraging machine learning algorithms, deep learning models, and radiomics, AI improves the accuracy of tumor detection, staging, and treatment planning while reducing diagnostic delays. The integration of AI into radiology workflows offers palliative care teams actionable insights, enabling tailored interventions that align with patients’ unique disease profiles and quality-of-life goals. This article reviews current methods, evaluates outcomes from recent studies, and discusses the implications of AI-driven imaging for the future of palliative oncology.