A Research Report on Interpretable Knowledge-Based Reasoning for Traditional Chinese Medicine Diagnosis

This research report examines an interpretable, knowledge-based reasoning paradigm for Traditional Chinese Medicine (TCM) diagnosis. Unlike data-driven or black-box predictive models, this work formalizes TCM diagnosis as a structured reasoning problem involving relationships among symptoms, mechanisms, patterns, and therapeutic principles. The report analyzes a framework based on explicit knowledge representation and graph-based inference, emphasizing transparency and auditability for educational and clinical decision-support contexts.