Harmonizing Vietnamese traditional and western medicine: a digital health blueprint and the IMKE architectural...

The concurrent use of traditional and Western medicine is a global healthcare reality. In countries like Vietnam, dual-paradigm clinical guidelines actively mandate integrated treatments for high-prevalence chronic diseases. However, safe integration at the point of care is severely hindered by data fragmentation, profound epistemological differences, and a critical "shadow pharmacovigilance" crisis regarding underreported herb-drug interactions (HDIs). This paper analyzes the state-of-the-art of Artificial Intelligence (AI) in integrative healthcare and proposes the Integrative Medicine Knowledge Engine (IMKE), a novel architectural blueprint designed to safely bridge Vietnamese traditional medicine (VTM) and Western biomedicine. Shifting from siloed technical models to a clinical-first perspective, the IMKE conceptualizes a three-stage digital health pipeline: (1) advanced medical text mining to digitize unstructured traditional practitioner notes; (2) an Integrative Knowledge Graph (IKG) that maps holistic VTM diagnostic patterns to Western pharmacological databases and ICD-10 standards; and (3) an AI-driven Clinical Decision Support System (CDSS) for proactive HDI safety monitoring. We illustrate this architectural data flow through three clinical scenarios-Essential Hypertension, Type 2 Diabetes, and Rheumatoid Arthritis. These scenarios demonstrate the system's theoretical capacity to retrieve culturally appropriate treatments, identify cross-paradigm therapeutic synergies, and generate explainable, mechanistic safety alerts that augment physician judgment while mitigating clinical alert fatigue. Ultimately, the IMKE framework provides a scalable, culturally inclusive roadmap for digital health. By translating centuries of experiential medical wisdom into an interoperable, computationally safeguarded infrastructure, this blueprint sets the foundation for evidence-based integrative care, future retrospective clinical validation, and enhanced patient safety.