分析
中国
大数据
聚类分析
数据科学
中医药
佣金
生物
地理
医学
计算机科学
业务
数据挖掘
替代医学
人工智能
考古
财务
病理
作者
Yaqun Liu,Chunjuan Zhou,Yukai Wan,Yongping Huang,L. Chen,Yang Yu,Biting Fang,Zhenxia Zhang,Chengsong Xie,Yicun Chen,Mouquan Liu,Yuzhong Zheng
摘要
This study employs big data analytics to explore the characteristics and association patterns of 102 Chinese food-medicine homologous (CFMH) species recognized by the National Health Commission of China, focusing on their medicinal attributes, flavors, associated meridians, and geographical distributions. Our findings reveal that most CFMH species originate from plants, particularly fruits and rhizomes, and are predominantly characterized as warm or neutral with a sweet flavor profile. Significant geographical clustering was identified in southern China, with notable associations between specific CFMH species and therapeutic meridians, supporting potential pathways for therapeutic applications. The integration of traditional Chinese medicine insights with modern big data analytics offers a powerful approach to understanding and leveraging the multifunctional nature of CFMH species. This study enhances our knowledge of CFMH species' characteristics and their potential health benefits, providing a foundation for further scientific exploration and application in healthcare. © 2025 Society of Chemical Industry.
科研通智能强力驱动
Strongly Powered by AbleSci AI