What are the stages of the AI lifecycle in healthcare?

The AI lifecycle comprises: Development (problem formulation, data curation, model training with bias audits and model cards), Validation (internal cross-validation, external validation on independent datasets, and prospective silent-mode/shadow validation), Deployment (integration into EHR systems with phased rollout, human-in-the-loop design, and fallback pathways), and Post-deployment monitoring (continuous tracking of performance metrics, drift detection, and predefined triggers for retraining or withdrawal).