Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Objective: To explore the prescription rules in treating liver cirrhosis's based on poison phlegm blood stasis and deficiency. Method: Clinical data of patients, who had been diagnosed with liver cirrhosis, was gathered. The data had been extracted, transformed and loaded through data integration and remittance, then, the data was analyzed by data classification, association, clustering and other large data analysis methods. Results: The prescription rules based on poison phlegm blood stasis and deficiency showed that according to medication frequency, detoxification drugs commonly used ArtemisiacapillarisThunb, Coptis chinensis Franch, Forsythia suspensa, Hedyotis diffusa Willd, and Scutellaria baicalensis Georgi, eliminating phlegm drugs commonly used Semen Coicis, Citrus aurantium L, Pinellia ternate, Pericarpium Citri Reticulatae and Trichosanthes kirilowii Maxim, removeing blood stasis drugs commonly used Radix Salviae Miltiorrhiae, Radix Curcumae, Rhizoma Curcumae, Herba Lycopi and Pollen Typhae, reinforcing deficiency drugs commonly used Poria, Carapax Trionycis, Rhizoma Atractylodis Macrocephalae, Radix Astragali seu Hedysari and Radix Codonopsis (Radix Pseudostellariae) . The selection of herbal medicine for poison in traditional Chinese medicine (TCM) is not only cold in property, bitter in flavor, but also converges to liver, gallbladder, spleen and stomach channel.The selection of herbal medicine for phlegm in TCM is not only warm in property, pungent in flavor, but also converges to spleen and lung channel. The selection of herbal medicine for blood stasis in TCM is not only cold in property, bitter in flavor, but also converges to liver, heart and spleen channel. The selection of herbal medicine for deficiency in TCM is not only mild in property, sweet in flavor, but also converges to spleen, liver and kidney channel. Conclusion: The syndrome differentiation and treatment of liver cirrhosis in Liver Institute of Hubei Provincial Hospital of Traditional Chinese are mainly based on poison phlegm blood stasis and deficiency.