The growing availability of wearable devices, digital health records, and consumer health applications has created unprecedented volumes of personal health data. However, most individuals lack tools to integrate these data streams into actionable insights that support preventive healthcare and collaboration with clinicians. Recent advances in generative and agentic artificial intelligence enable systems capable of autonomously organizing information, generating insights, and assisting decision-making. This study proposes an architecture for agentic AI systems designed to support personal health management (PHM) by integrating diverse health data sources and delivering personalized insights and clinical summaries.

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