BEIJING, CHINA / RankWire.AI / – Artificial intelligence is increasingly permeating traditional Chinese medicine education, research initiatives, and clinical applications throughout China. Beijing University of Chinese Medicine has created a dedicated large model centered on comprehensive TCM knowledge and educational resources. The Xinhuo TCM system encompasses classical texts, medical theories, herbal data, prescriptions, and teaching materials. Its initial version was launched in 2025, with further enhancements made during 2026.
According to the university, Xinhuo TCM now functions as a 70-billion-parameter system built atop leading Chinese artificial intelligence platforms. Developers designed the model to facilitate learning, teaching, research, administrative tasks, and international communication related to traditional Chinese medicine. Students can pose questions about herbal combinations and receive detailed explanations of formulas and their fundamental principles. Additionally, the university has developed an intelligent robot that demonstrates traditional massage techniques for hands-on training.
China’s broader application of AI within traditional Chinese medicine also extends to medical knowledge management and clinical decision-making tools. Digital systems are capable of organizing historical medical literature and structuring insights from experienced practitioners for educational and research purposes. Researchers are exploring artificial intelligence for diagnostic data, pre-consultation systems, and other decision-support functions. These efforts reflect a wider initiative to link traditional medical knowledge with modern data processing and computing technology.
China builds digital infrastructure to support TCM development
For the 2026 to 2030 period, China incorporated artificial intelligence into its national strategy for traditional medicine growth. The National Administration of Traditional Chinese Medicine alongside the National Development and Reform Commission issued the plan in July. It emphasizes the creation of high-quality AI datasets tailored specifically for the traditional Chinese medicine industry. The plan also advocates for developing digital infrastructure, intelligent hospitals specializing in traditional medicine, and smart diagnostic support at primary healthcare centers.
This national framework prioritizes data governance alongside the expansion of AI tools within the traditional medicine sector. It promotes enhanced data classification, protection, and compliant circulation across healthcare, research, and related digital services. The authorities also aim to increase the adoption of standardized intelligent equipment and digital technologies in traditional Chinese medicine. These measures encompass clinical services, education, scientific research, and the management of traditional medicine data.
Artificial intelligence transitions from academic settings to clinical practice
Research published in 2026 investigated the performance of large language models within traditional Chinese medicine healthcare environments. One study assessed an AI pre-consultation system at a tertiary traditional medicine hospital, noting initial acceptance by physicians. Medical professionals responded more favorably to its ability to gather information prior to consultations than to its decision-support functions. Researchers identified remaining challenges related to complaint collection, workflow integration, documentation requirements, and accessibility for elderly patients.
Recent developments demonstrate AI’s expanding role across various sectors of China’s traditional Chinese medicine system. Xinhuo TCM has obtained national registration for generative AI services, integrating this specialized model into China’s regulatory framework for public AI offerings. Current implementations include education, research, knowledge management, hospital workflows, and auxiliary diagnostic tools. China’s 2026 to 2030 TCM development plan now officially incorporates artificial intelligence datasets and digital health infrastructure as vital components for the sector’s growth.