Artificial intelligence is in-depth integration with the field of traditional Chinese medicine. From April 23 to 24, a series of major measures were released at the 4th High-Quality Development Conference of Traditional Chinese Medicine held in Wuzhen, Zhejiang, including the first release of the Aireview Agent of the Chinese Medicine evidence-based evaluation agent, the group standards of the "Specifications for the Construction of Research-based Pharmacy in Clinical Efficacy Treatment Data Acquisition and Research on Traditional Chinese Medicine", and the "2025 International High-Impact Research on Traditional Chinese Medicine and Traditional Chinese Medicine".

It is reported that the conference is sponsored by the National Key Laboratory of Modern Traditional Chinese Medicine Creation and Tianjin University of Traditional Chinese Medicine, and hosted by the Modern Traditional Chinese Medicine Haihe Laboratory and the National Modern Traditional Chinese Medicine Innovation Center. The conference focused on the theme of "Traditional Medicine + Artificial Intelligence", focusing on the application needs of AI in clinical diagnosis and treatment, scientific research, talent training, industrial development, etc., discussing the development strategies and key tasks of traditional Chinese medicine in the intelligent era, and providing intellectual support for the formulation of relevant policy plans. Academicians of the Chinese Academy of Engineering Zhang Boli, Huang Luqi, Chen Xiangmei, Wang Qi, Tian Jinzhou, and Zhu Liguo, former deputy director of the State Drug Administration, Zhao Junning, Secretary-General of the Chinese Society of Traditional Chinese Medicine Li Zongyou, Party Secretary of Tianjin University of Traditional Chinese Medicine Liu Gesheng, and nearly 100 representatives of well-known experts from the fields of education, medical care, science and technology, industry, etc. attended the meeting online and offline. Academician Huang Luqi, Academician Zhang Boli and Secretary Liu Gesheng delivered opening speeches, and Academician Zhu Liguo and Professor Zhang Junhua presided over the opening ceremony and launch ceremony of the conference respectively.

Academician Zhang Boli delivered a speech

"Traditional Medicine + Artificial Intelligence Wuzhen Consensus" released

Technology changes the world and affects the future. Based on in-depth thinking on the relationship between "technology-business-industry", we have formed the "Traditional Medicine + Artificial Intelligence Wuzhen Consensus" and officially released it at the meeting after cross-domain experts' discussion. The Consensus proposes:

1. Embrace AI. Fully understanding of the characteristics of AI technology is the prerequisite for rational use. AI technology is in the process of continuous iteration and development, and has shown a powerful force to promote the development of new quality productivity. Looking to the future, AI will also strongly promote the leapfrog development of traditional Chinese medicine. This requires the traditional Chinese medicine community to strengthen strategic planning in terms of ideological understanding, condition construction and talent training.
2. Develop AI. AI must be closely integrated with the needs of the development of traditional Chinese medicine to generate new momentum. The general big model cannot meet the needs of the development of the traditional Chinese medicine industry. It is necessary to strengthen top-level design and overall coordination, strengthen cross-innovation research on disciplines, explore traditional Chinese medicine knowledge, focus on data quality and standardization construction, and develop traditional Chinese medicine industry models and professional intelligent bodies.
3. Apply AI. Strengthen the scenario research of AI in traditional Chinese medicine, and promote innovation and development through application. There are broad scenarios for AI application in all fields such as traditional Chinese medicine, education, science and technology, industry and management. It is necessary to improve the mechanism of co-construction, sharing and win-win, strengthen policy guarantees and project guidance, promote the linkage of "government, industry, academia, research and application" to form a new business model of traditional Chinese medicine + AI.

The "Consensus" calls on experts, scholars, entrepreneurs and management departments in various fields such as traditional Chinese medicine, artificial intelligence, and medical engineering to strengthen coordination and jointly contribute to the high-quality development of traditional Chinese medicine in the intelligent era.

"Traditional Medicine + Artificial Intelligence Wuzhen Consensus" released on the scene

The first release of the Aireview Agent for the Chinese Medicine

The Aireview Agent was also released for the first time at the meeting. Relying on the national interdisciplinary innovation team of traditional Chinese medicine intelligent production and transformation, technical support is provided by experts from Tianjin University of Traditional Chinese Medicine, Haihe Laboratory of Modern Traditional Chinese Medicine, National Supercomputing Tianjin Center, Institute of Automation of the Chinese Academy of Sciences, Nankai University, and Tianjin University. Through the integration of artificial intelligence technology, big data analysis technology and evidence-based medical methods, it is fine-tuned based on Tongyi Qianwen and DeepSeek domestic deep reasoning big models, and developed the "Traditional Medicine Evidence-based Evaluation Agent". This agent embodies the entire process and in-depth understanding of the evidence transformation needs, and can search, extract, check, evaluate, analyze and personalized output, truly realizing personalized and intelligent evidence production.

Zhang Junhua, vice president of Tianjin University of Traditional Chinese Medicine, said that the production and transformation of traditional Chinese medicine evidence goes through three stages: one is the artificial dispersion stage, where researchers need to manually retrieve, extract and analyze data from a large number of scattered databases, which has problems such as time-consuming, low efficiency, and poor quality consistency; the other is the database concentration stage, the evidence-based medical team of Tianjin University of Traditional Chinese Medicine adopts the "human sea tactic" and took 8 years to build the "Traditional Medicine Evidence Database System (EVDS)", which realizes the concentration of clinical evidence sources, solves the problem of resource database construction, and improves application efficiency, but the evidence transformation process still relies on manual labor, and the personalized data call program is complex. The successful development of the "Airview Agent for Traditional Chinese Medicine" marks the third stage of transformation of clinical evidence in traditional Chinese medicine.

Aireview Agent released on the site

The group standards of the "Specifications for the Construction of Research-based Pharmacy Clinical Efficacy Treatment Data Collection Research Pharmacy" of the Chinese Society of Traditional Chinese Medicine were also released on the same day, as well as the 2025 international high-influence research on traditional Chinese medicine and traditional medicine. The 50 high-influence research selected this time involved 7 research fields.

"2025 International High-Influence Research on Traditional Chinese Medicine and Traditional Medicine" released on the site

During the conference, three special seminars were also held. The experts at the conference focused on the opportunities and challenges of AI for the high-quality development of traditional Chinese medicine and industry, the opportunities and challenges of traditional Chinese medicine scientific and technological innovation and talent training in the intelligent era, as well as challenges and countermeasures of the traditional Chinese medicine industry, and formed a number of consensuses, which had important practical guidance and strategic value.

[Editor in charge: Sun Hui]