DFGLM-TCM: an integrated knowledge-and experience-driven large language model system for Traditional Chinese Medicine practice

Traditional Chinese Medicine (TCM) clinical practice depends on both codified theoretical knowledge and practitioner-specific experience, which differ in their data sources, reasoning patterns, and scope of generalization. We developed DFGLM-TCM, a modular large language model-based service system that separately models these two knowledge types through task-oriented components and coordinates them within a unified multi-task architecture. The knowledge-oriented component integrated a curated 22-GB TCM corpus containing approximately 3 million structured entries, a manually validated knowledge graph with more than 200,000 entities, and retrieval-augmented generation for literature retrieval and general TCM question answering. The experience-oriented component was trained using approximately 5000 authentic outpatient records from a senior TCM practitioner and 2000 expert-reviewed augmented cases to provide practitioner-specific diagnostic and prescription references. Through standardized interfaces and role-based access, the system supports knowledge retrieval, question answering, structured consultation, and prescription reference for clinicians, patients, and students. In an expert-rated evaluation of 100 TCM knowledge questions, DFGLM-TCM achieved the highest descriptive mean score among the evaluated models (4.48 ± 0.76). In 454 independent pulmonary-nodule cases, the experience-oriented component achieved a prescription-consistency score of 8.95 ± 0.63, exceeding that of the model additionally trained with general TCM knowledge (7.52 ± 0.44). A one-month assessment involving 35 physicians at three primary-care institutions suggested favorable short-term usability and acceptance. These findings highlight the value of separating general TCM knowledge from practitioner-specific experience while coordinating task-oriented training and multi-task services within a unified system, and support further evaluation of DFGLM-TCM as an auxiliary reference tool in broader clinical settings.

Authors

Institutions

Publication Details

Journal
Chinese Medicine
Published
2026-08-28
DOI
https://doi.org/10.1186/s13020-026-01512-y
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DFGLM-TCM: an integrated knowledge-and experience-driven large language model system for Traditional Chinese Medicine practice

Lei Gao, Dianna Liu, Zilin Song, Ruikang Zhong et al.
Chinese Medicine
Traditional Chinese Medicine Studies
article

DFGLM-TCM: an integrated knowledge-and experience-driven large language model system for Traditional Chinese Medicine practice

Lei Gao, Dianna Liu, Zilin Song, Ruikang Zhong, Min Jiang, Pengfei Jia, Siyi Chen, Yuewen Dai, Yue Sun, Yisha Su, Zexing Li, Zhixing Li, Kaiwen Hu, Wenzheng Zhang, Le Zhang
article en

Abstract

Traditional Chinese Medicine (TCM) clinical practice depends on both codified theoretical knowledge and practitioner-specific experience, which differ in their data sources, reasoning patterns, and scope of generalization. We developed DFGLM-TCM, a modular large language model-based service system that separately models these two knowledge types through task-oriented components and coordinates them within a unified multi-task architecture. The knowledge-oriented component integrated a curated 22-GB TCM corpus containing approximately 3 million structured entries, a manually validated knowledge graph with more than 200,000 entities, and retrieval-augmented generation for literature retrieval and general TCM question answering. The experience-oriented component was trained using approximately 5000 authentic outpatient records from a senior TCM practitioner and 2000 expert-reviewed augmented cases to provide practitioner-specific diagnostic and prescription references. Through standardized interfaces and role-based access, the system supports knowledge retrieval, question answering, structured consultation, and prescription reference for clinicians, patients, and students. In an expert-rated evaluation of 100 TCM knowledge questions, DFGLM-TCM achieved the highest descriptive mean score among the evaluated models (4.48 ± 0.76). In 454 independent pulmonary-nodule cases, the experience-oriented component achieved a prescription-consistency score of 8.95 ± 0.63, exceeding that of the model additionally trained with general TCM knowledge (7.52 ± 0.44). A one-month assessment involving 35 physicians at three primary-care institutions suggested favorable short-term usability and acceptance. These findings highlight the value of separating general TCM knowledge from practitioner-specific experience while coordinating task-oriented training and multi-task services within a unified system, and support further evaluation of DFGLM-TCM as an auxiliary reference tool in broader clinical settings.

Chinese MedicineVol. 21(1)
Beijing University of Chinese Medicine (CN), Zhong Ke San Huan (China) (CN), Beijing Fengtai Hospital (CN)
Beijing University of Chinese Medicine, Key Technologies Research and Development Program
Quality Education
Openalex Percentile: Top 6%
Traditional Chinese Medicine Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.