Mini-review summarizes AI applications for cancer pain assessment and management
This mini-review summarizes recent applications of artificial intelligence across multiple dimensions of cancer pain management in patients with cancer. The review describes AI's potential roles in pain assessment, analgesic decision-making, remote follow-up, and interventional planning. It notes 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. Specific study designs, sample sizes, comparators, and quantitative effect measures are not reported.
The review discusses methodological and real-world challenges for AI implementation in this clinical domain. Safety and tolerability data for AI applications are not reported. Key limitations include the descriptive nature of the review, lack of reported primary outcomes or quantitative synthesis, and unspecified funding or conflicts of interest.
For practice, this work provides a conceptual overview of how AI may contribute to an integrated, longitudinal management framework for cancer pain. However, the evidence remains preliminary and narrative. Clinicians should recognize this as a summary of emerging applications rather than evidence of established efficacy or safety. Real-world implementation faces significant methodological hurdles that require further investigation.
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