Under the global background of the accelerated reconstruction of the smart healthcare ecosystem, artificial intelligence technology is deeply driving the transformation of the healthcare paradigm from experience-driven to data-knowledge dual-wheel driven. As a treasure of Chinese civilization, the core value of traditional Chinese medicine lies in the individualized diagnosis and treatment system based on "syndrome differentiation and treatment". The integration of multimodal diagnosis and treatment data and the construction of intelligent decision-making models will become the key path to break through the bottleneck of the modernization of traditional Chinese medicine. This research is based on the strategic orientation of "Healthy China 2030" and relies on the national science and technology major project of the team. It explores the establishment of a "three-stage four-dimensional" model of "data layer - knowledge layer - decision-making layer" and "feature extraction - relationship reasoning - dynamic correction - clinical verification" through a closed-loop verification mechanism of "human-machine collaboration - knowledge iteration", to promote the digital and intelligent transformation of traditional Chinese medicine.
Citation： QIAN Zhenzhen, DAI Xinyue, ZHANG Haoling, ZHANG Guoyuan, LI Jinsheng, GAO Rui, LU Yan. Construction of an intelligent decision-making model for traditional Chinese medicine syndrome differentiation and treatment based on multimodal data fusion: research on optimization of diagnosis and treatment pathways driven by deep learning. Chinese Journal of Evidence-Based Medicine, 2026, 26(1): 93-97. doi: 10.7507/1672-2531.202505067 Copy
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