Beyond the algorithm: why oncology nursing in Asia-Pacific needs evidence-based AI evaluation A nurse working in a busy oncology ward in Manila receives an alert from a newly installed artificial intelligence (AI) clinical decision support system.The tool recommends adjusting the symptom management plan for a patient undergoing chemotherapy for gastric cancer.The algorithm's confidence score is high.But how does she know whether to trust it?Has this tool been validated on Filipino patients?Has anyone evaluated whether it improves the outcomes she cares about most, patient comfort, timely intervention, safe care transitions?These are not hypothetical questions.They represent the daily reality confronting oncology nurses across the Asia-Pacific as AI tools proliferate in cancer care settings.We argue that the rapid adoption of AI in oncology across the Asia-Pacific region has dramatically outpaced the evidence base required to guide its responsible use.Oncology nurses must demand and lead rigorous, context-sensitive evaluation of these tools.Moving beyond technical accuracy to determine whether AI improves cancer care in diverse clinical environments of our region.Achieving this goal requires methodological innovation, drawing upon pragmatic trials, hybrid designs, real-world evidence (RWE), and health technology assessment (HTA) frameworks that can accommodate the unique characteristics of AI-based health interventions.
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