Health AI Safety Governance

Design a governance framework for health-information AI that prioritizes patient safety, data provenance, model explainability, accountability, and alignment with regulatory expectations. Include evaluation protocols, risk management, human-in-the-loop design, incident response, certification pathways, and ongoing monitoring. Compare alternative governance models and provide a practical, stepwise roadmap for adoption within healthcare organizations and research institutions.