AI applications across the cancer pain care Continuum: applications and future directions

Given the rapid expansion of AI applications across multiple dimensions of cancer pain management, there is an urgent need to synthesize current evidence and clarify future directions to guide clinical and research practice. Cancer pain remains one of the most central and challenging issues in pain medicine. Its pathogenesis is multifaceted, involving tumor invasion, treatment-related injury, and diverse biopsychosocial factors; assessment is difficult, treatment decisions involve numerous variables, and long-term management is resource-intensive. Epidemiological data indicate that approximately half of all patients with cancer experience moderate-to-severe pain during the disease course, with the burden markedly higher in advanced stages. The rapid advancement of AI in medicine has spurred growing interest in its potential contributions to cancer pain assessment, analgesic decision-making, remote follow-up, and interventional planning. This mini-review, organized from a clinical care-pathway perspective, summarizes recent applications of AI in cancer pain assessment, opioid management, remote monitoring, and interventional or longitudinal care. We further discuss methodological and real-world challenges, emphasizing how AI may ultimately contribute to an integrated, longitudinal management framework for cancer pain.