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These layers leverage multi-omics data, EEG sleep microstructure, real-time sensors, and EMR feeds to create a dynamic, patient-specific architecture. Uncertainty-aware explainable AI (XAI) modules ensure privacy and interpretability, enabling causal inference through advanced machine learning techniques. Adaptive care pathways, including precision pre-\/post-biotic delivery and circadian light prescriptions, are optimized via nurse-in-the-loop reinforcement learning. The digital twin is operationalized through a five-step closed-loop workflow in hospital and community settings. Quantum-accelerated simulations and a proposed RCT (D-TWIN-RCT) will assess efficacy compared to standard care. Social, legal, and ethical frameworks protect data sovereignty and autonomy. 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