JCNRJournal of Clinical and Nursing Research2208-36852208-3693Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jcnr.v10i2.14196ArticleHolistic Hierarchical Predictive-Integration Theory (HHPIT): An Exploration of AI-Empowered Innovation and Empirical Research in Traditional Chinese Medicine Meridian Theoryhttps://artdesignp.com/journal/JCNR/10/2/10.26689/jcnr.v10i2.14196ZhangJiren,ZhangYang,HaoBingna,HaoJunjie,WangLeiming,LaoFengtian20261022026-03-11By 2025, research on Traditional Chinese Medicine (TCM) meridians has generated 12–15 macro-level theories and over 20 specific hypotheses, manifesting a highly fragmented research landscape. Objective: This paper proposes the “Holistic Hierarchical Predictive-Integration Hypothesis” (HHPIT) to construct a unified theoretical framework that integrates the rational components of existing meridian hypotheses. Methods: The HHPIT hypothesis systematically reviews current meridian theories, employs interdisciplinary methodologies, integrates artificial intelligence technology, and establishes a three-tier architecture encompassing structural, functional, and systemic layers. Results: HHPIT successfully integrates diverse meridian theories, proposes a computable algorithmic pipeline, and provides specific application protocols for chronic disease treatment, anti-aging, and enhancement of Zang-fu organ functions. Conclusion: HHPIT offers a novel, computable, and verifiable research paradigm for meridian studies, promoting the modernization and internationalization of TCM theory.

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