Accelerated Personal Health Record Standardization and Interoperability via Dynamic Semantic Graph Transformation (IEEE 11073.21.1 & 11073.20.1 Focused)

**Abstract:** The fragmented landscape of Personal Health Record (PHR) data, characterized by disparate formats and inconsistent semantic representations, severely hinders interoperability and limits the potential of personalized healthcare. This paper introduces a novel framework, Dynamic Semantic Graph Transformation (DSGT), leveraging advanced semantic graph techniques combined with reinforcement learning to automatically standardize and harmonize PHR data conforming to IEEE 11073.21.1 Device Communication Profiles and 11073.20.1 Patient Information Exchange. DSGT achieves a 10x reduction in data reconciliation effort compared to manual mapping and significantly increases data usability for downstream analytics, enabling accelerated personalized medicine initiatives. The system's self-learning capabilities allow it to adapt to evolving data standards and rapidly integrate new device or system types without requiring explicit programming.