The prominent feature and form of clinical diagnosis and treatment of traditional Chinese medicine is individualization, which has generated difficulty for clinical evaluation and has restricted the production of high-level evidence for traditional Chinese medicine for a long time. Based on the complexity and dynamics of individualized information under the characteristics of time and space, this paper references the theory of space-time of system science to analyze the individualized data of diagnosis and treatment of traditional Chinese medicine and summarizes the concept of the long time course for clinical evaluation. Based on the concept of the long time course, this paper starts with the origin of clinical evaluation, which is the construction of clinical problem elements named PICO, introduces dynamic evaluation factors, explores the construction of individualized dynamic evaluation method of traditional Chinese medicine, and provides demonstration and examples for the design and implementation of individualized clinical research in future.
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.