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        <datestamp>2026-10-01T05:29:09Z</datestamp>
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          <dc:title>Data Sheet 1_Harmonizing Vietnamese traditional and western medicine: a digital health blueprint and the IMKE architectural framework.pdf</dc:title>
          <dc:creator>Anh Nguyen Thi Dieu (25152456)</dc:creator>
          <dc:creator>Hieu Le Ngoc (25152459)</dc:creator>
          <dc:subject>Health Informatics</dc:subject>
          <dc:subject>clinical decision support systems (CDSS)</dc:subject>
          <dc:subject>digital health</dc:subject>
          <dc:subject>herb-drug interactions (HDIs)</dc:subject>
          <dc:subject>integrative medicine</dc:subject>
          <dc:subject>medical informatics</dc:subject>
          <dc:subject>pharmacovigilance</dc:subject>
          <dc:subject>Vietnamese traditional medicine (VTM)</dc:subject>
          <dc:description>&lt;p&gt;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.&lt;/p&gt;</dc:description>
          <dc:date>2026-10-01T05:29:09Z</dc:date>
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          <dc:identifier>10.3389/fdgth.2026.1928965.s001</dc:identifier>
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          <dc:rights>CC BY 4.0</dc:rights>
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