TCM LLM · Surveys
TCM LLM surveys
Surveys of Traditional Chinese Medicine large language models: knowledge organization, assisted diagnosis, multimodal four examinations, agents, and evaluation.
从大语言模型到智能体（兰州大学学报医学版综述）
Chinese-language systematic review organized around the LLM-to-agent transition for TCM clinical assisted diagnosis and treatment (J. Lanzhou Univ. Med. Sci. 2026;52(4):49-57).
Agentic and Knowledge-Grounded LLMs in TCM（预注册）
OSF preregistration (not a completed review) of a systematic review on agentic and knowledge-grounded LLMs in TCM: evidence mapping, text mining, and translation readiness.
中医大模型关键技术综述（IJPRAI）
Survey of key technologies for TCM LLMs: knowledge organization, aided diagnosis, and clinical decision support (formally published in IJPRAI, World Scientific).
AI驱动中医诊断智能化综述（JTCMS）
Survey on multimodal fusion and LLMs for intelligent four-diagnosis in TCM: applications, challenges and outlook (JTCMS).
人工智能驱动下的中医智能诊疗研究进展与挑战
Chinese review structured on the six-step TCM diagnosis-treatment chain (four diagnoses, pattern differentiation, prescription, outcome prediction), contrasting supervised/unsupervised/RL/deep-learning paradigms (Shanghai J. TCM 2026;60(1)).
Cong H et al. TCM×LLM 综述（OSF 预印本）
OSF-preprint review of LLMs in TCM (not peer-reviewed; archival).
Cai R et al. TCM×LLM scoping review（OSF 预印本）
OSF-preprint scoping review of LLMs in TCM (not peer-reviewed; archival).
AI in TCM: multimodal data to pharmacology and clinical decision（PRMCM 综述）
Broad AI-in-TCM review from multimodal data integration to pharmacological research and clinical decision support (Pharmacol. Res. Mod. Chin. Med. 2026; found in the third-round scan).
LLM-Based Multi-Agent Systems for Clinical Workflows（ACL 2026，邻近）
Adjacent ACL 2026 survey of workflow-level multi-agent clinical systems with a four-layer evaluation stack; no TCM coverage but methodologically isomorphic process-evaluation claims.
医学大语言模型的研发与应用系统综述（智能系统学报，邻近）
Adjacent systematic review of 129 medical-domain LLMs (to 2024-06) and four clinical application categories; methodologically comparable search protocol.
医疗领域的大型语言模型综述（智能系统学报，邻近）
Adjacent Chinese general survey of medical LLMs (training pipeline, strategies, scenarios, challenges), a superset-context reference for TCM LLM surveys.
Intelligent Question-Answering Systems in Healthcare（Healthcare，邻近）
Adjacent review (not TCM-specific): 2018-2025 healthcare QA survey with CiteSpace bibliometrics, explicitly covering TCM formula-development scenarios (Healthcare 2025).
人工智能实现中医四诊的发展现状、问题及解决路径（中华中医药学刊）
Short Chinese review of AI-based four-diagnosis objectification: face/tongue acquisition, electronic nose, pulse sensing, and low fusion of multi-diagnosis data (bibliographic record only).
人工智能赋能中医数字化诊断：现状与挑战（中华中医药学刊）
Short Chinese review of AI-empowered digital TCM diagnosis: applications, data-quality, interpretability, and theory-integration challenges (bibliographic record only).
AI for Spleen-Stomach Disorders in TCM（Curr Med Sci）
Single-disease-area (spleen-stomach) review of KG plus intelligent diagnosis/treatment with a symptom-syndrome-disease-formula framework (Curr. Med. Sci. 2025;45(6)).
AI and Big Data in TCM Standardization and Internationalization（Chin Med Cult）
Perspective on AI and big data for TCM standardization and internationalization (Chin. Med. Cult. 2026, ahead of print).
AI empowers the innovation of TCM（J Integr Med 评论）
Single-author perspective on AI for TCM innovation: classics mining, diagnosis standardization, drug R&D cycles (J. Integr. Med. 2026).
古籍知识图谱×多智能体融合综述（Chin Med）
Challenges-and-prospects review of knowledge-graph construction over ancient TCM classics, first to frame multi-agent convergence in this area (Chin. Med. 2025;20:168).
The integration of machine learning into TCM（J Pharm Anal）
Review of machine-learning integration into TCM along diagnostic objectification and mechanism-elucidation lines (J. Pharm. Anal. 2025;15(8):101157).
Deep learning in TCM（J Integr Med）
Single-technology review of deep learning in TCM: medical imaging, herbal material research, data mining (J. Integr. Med. 2026;24(4):471-480).
AI in TCM: Unraveling Herbal Medicine's Mechanisms（Research）
Broad AI-in-TCM review arguing AI should move beyond correlational analysis toward reconstructing the biological logic of syndrome differentiation and formula compatibility (Research 2026;9:1224).
多模态大模型驱动舌脉面诊智能化综述（Springer 书章）
The only review text dedicated to multimodal-LLM-driven tongue, pulse, and facial diagnosis in TCM (Springer CCIS book chapter; weaker peer review than journals).
Lukman et al. 2007: 中医计算方法综述
Foundational survey of computational methods for TCM (expert systems, ML, data mining).
Gu & Chen 2013: 生物信息学遇见中医
Historical review of bioinformatics meeting TCM (omics and text mining).
Zhao et al. 2015: 中医患者分类进展（ML 视角）
Review of ML-driven advances in patient classification for TCM.
Chu et al. 2020: 中医定量知识表示模型综述
Review of quantitative knowledge representation models of TCM (ontologies, rules, statistics).
Zhang et al. 2021: 计算中医诊断文献综述
Literature survey of computational TCM diagnosis — symptom acquisition, pattern modeling, and systems.
Tian et al. 2024: 四诊机器学习综述
Review of machine learning for TCM four diagnoses — inspection, auscultation-olfaction, inquiry, and palpation.
Qu et al. 2024: 中医知识图谱综述
Review of knowledge graphs in TCM — analysis, construction, applications, and prospects.
Song et al. 2024: AI 辅助中医辨证关键问题与技术挑战
Strategic-study review of key issues in AI-assisted TCM syndrome differentiation — multimodal fusion, symptom association, pattern quantification and reasoning, and TCM LLMs.
Su et al. 2024 — Review of AI in TCM diagnosis and treatment (Chinese)
Chinese-language review of three AI stages in TCM care — expert systems, ML, and deep learning — with challenges.
Li et al. 2024 — Research progress and prospects of LLMs in TCM (Chinese)
Chinese-language review of TCM LLM pipelines, frontier techniques (prompting/RAG/RLHF), and application prospects.
Yip et al. 2025: 中西医结合 LLM 进展与挑战
Review of LLMs in integrative medicine — progress, challenges, and opportunities.
Wang et al. 2025: AI 驱动中医诊断模型进展
Systematic review of AI-driven TCM diagnostic models (four-diagnosis objectification, pattern differentiation).
Meng et al. 2025: 大模型+虚拟细胞助力中医变革
Review of large models and virtual cells aiding modern analysis of stroke treatment with TCM formulas.
Zhang et al. 2025: 中医 LLM 短综述与展望
Short survey and outlook on TCM LLM models and tasks.
Shataer et al. 2025: LLM 在中医应用（State-of-the-Art Review）
State-of-the-art review scanning TCM LLM application scenarios (care, education, translation, research).
Guo et al. 2025: GPT 能否加速中医智能诊疗（综述+实证）
Survey plus empirical analysis of whether GPTs can accelerate intelligent TCM diagnosis and treatment.
Chen et al. 2025: 中医大语言模型系统综述
Systematic review of 10 studies (to mid-2024) on LLMs in TCM generative tasks.
Ren et al. 2025: 中医大语言模型（Scoping Review）
Arksey-O'Malley scoping review (29 studies to 2024-04) covering knowledge management, assisted care, and exam accuracy.
Lu et al. 2026: 深度学习中医诊断方法学质量审计
Systematic review and validation-gap analysis of deep learning for TCM disease diagnosis.
Wu et al. 2026: AI 在中药材中的应用综述
Full-stack survey of AI in TCM herbs — compounds, targets, quality control, with an LLM section.
Guo et al. 2026: AI 与多模态数据融合推动中医现代化
Panoramic AI review (ML/DL/KG/NLP/LLM) for TCM modernization with multimodal data integration.
Chen et al. 2026: LLM 在中医的下一步（叙述性综述）
Narrative review on the next step of LLMs in TCM — multimodality, agents, and clinical translation.
Xu et al. 2026: 基于 LLM 的中医智能问答系统综述
Review of intelligent TCM question-answering systems based on LLMs (KG-QA to LLM-QA and RAG).
Yao et al. 2026: LLM 与循证中医整合（Scoping Review）
PRISMA scoping review (12 studies, 2022-11 to 2026-01) on integrating LLMs with evidence-based Chinese medicine.
Han et al. 2026: LLM 在中医中的调优与临床应用（Scoping Review）
PRISMA-ScR scoping review (27 studies to 2025-05) on tuning (LoRA/CPT/RAG) and clinical application of TCM LLMs.