中医药
代表(政治)
基础(线性代数)
国家(计算机科学)
传统医学
计算机科学
医学
数学
自然语言处理
替代医学
算法
病理
政治学
几何学
政治
法学
作者
Wan‐Yang Sun,Rong Wang,Shu‐Hua Ouyang,Wanli Liang,Junwei Duan,Wenyong Gong,Lingling Hu,Xiujuan Chen,Yi-Fang Li,Hiroshi Kurihara,Xin‐Sheng Yao,Hao Gao,Rong‐Rong He
标识
DOI:10.1016/j.apsb.2025.03.009
摘要
"Weibing" is a fundamental concept in traditional Chinese medicine (TCM), representing a transitional state characterized by diminished self-regulatory abilities without overt physiological or social dysfunction. This perspective delves into the biological foundations and quantifiable markers of Weibing, aiming to establish a research framework for early disease intervention. Here, we propose the "Health Quadrant Classification" system, which divides the state of human body into health, sub-health, disease-susceptible state, and disease. We suggest the disease-susceptible stage emerges as a pivotal point for TCM interventions. To understand the intrinsic dynamics of this state, we propose laboratory and clinical studies utilizing time-series experiments and stress-induced disease susceptibility models. At the molecular level, bio-omics technologies and bioinformatics approaches are highlighted for uncovering intricate changes during disease progression. Furthermore, we discuss the application of mathematical models and artificial intelligence in developing early warning systems to anticipate and avert the transition from health to disease. This approach resonates with TCM's preventive philosophy, emphasizing proactive health maintenance and disease prevention. Ultimately, our perspective underscores the significance of integrating modern scientific methodologies with TCM principles to propel Weibing research and early intervention strategies forward.
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