Artificial Intelligence: A Catalyst for the Modernization of Traditional Chinese Medicine

Background The modernization of Traditional Chinese Medicine (TCM) has long faced significant bottlenecks, including an unclear material basis of efficacy, subjective diagnostic methods, and a lack of standardized evaluation. Artificial Intelligence (AI) offers promising tools to address these bottlenecks through data-driven approaches. Methods This scoping review systematically synthesizes literature up to 2025, obtained via searches in PubMed, Web of Science, and CNKI. Studies applying AI/ML techniques to TCM problems were included and analyzed across four key domains. Applications & Results AI demonstrates substantial potential in reshaping TCM: (1) Drug Discovery & Formula Optimization: Machine learning models enable high-throughput compound screening and formula recommendation, though often lack TCM-specific design. (2) Mechanism Elucidation: Knowledge graphs and multi-omics data integration help decode the "multi-component, multi-target" actions of TCM formulas. (3) Diagnostic Innovation: Deep learning and large language models (LLMs) demonstrate promising accuracy in tasks such as tongue image analysis and syndrome differentiation, in some studies approaching expert-level performance, thereby aiding standardization efforts. (4) Quality Control: AI-powered spectral and image analysis facilitates rapid, non-destructive assessment of herbal medicine quality. Challenges Critical barriers remain, including data heterogeneity, poor model interpretability ("black-box" issue), a significant translational gap, and a lack of interdisciplinary talent. Conclusion & Future Directions Although most current applications adapt generic AI algorithms, future progress hinges on developing TCM-aware models (e.g., symbolic-neural hybrids), establishing standardized TCM data ontologies, and conducting rigorous clinical validation. The deep integration of AI and TCM holism paves a new path for data-driven, precise TCM and contributes to a global integrated medical system.