摘要Artificial intelligence(AI)and big data are reshaping the healthcare landscape.However,clinical value depends on how well systems augment clinicians and fit into routine workflows.To this end,we introduce the TRIAD framework:trustworthy governance,real-world clinical value,and integrated adaptive deployment,to guide the development,validation,and deployment of clinical AI.TRIAD requires explicit data provenance and intended use,fairness auditing,and calibrated uncertainty.This framework evaluates the human-AI team in real workflows using team-level metrics,including accuracy,safety,workload,and patterns of acceptance,editing,and overriding.Deployment proceeds via staged rollouts with pre-registered guardrails and continuous monitoring of performance and subgroup impact.TRIAD views intelligence as a property of the human-AI team rather than the AI model alone.Aligning governance,evaluation,and deployment around clinicians and patients enables durable gains in safety,equity,efficiency,and experience,thereby elevating clinical value.