In Traditional Chinese Medicine (TCM), the diagnosis and treatment of diseases typically involve viewing the patient as a system and considering both the intrinsic natural mechanisms of the disease and the external sociological factors. However, a comprehensive and scientific standard for understanding the external sociological factors in TCM diagnosis and treatment has not yet been established. The main reason for this is the complexity of computing these sociological factors due to their openness, multidimensionality, and heterogeneity. Drawing insights from computational sociology, this study explores the latent sociological factors in TCM disease diagnosis and treatment. It aims to obtain sociological factor data related to diseases from various online sources, such as internet-based medical consultation platforms and social networks. Through data analysis, it seeks to reveal the correlations between diseases and sociological latent factors. The ultimate goal is to establish a pre-diagnosis sociological factor database for TCM diseases. This endeavor serves as a foundation for developing a more scientific online TCM disease consultation system, providing references for TCM disease diagnosis and treatment, and offering evidence-based health behavioral recommendations for disease prevention.
"Data Analysis of Traditional Chinese Medicine Disease Diagnosis from the Perspective of Computational Sociology.,"
International Journal of Computer and Communication Technology: Vol. 9:
2, Article 2.
Available at: https://www.interscience.in/ijcct/vol9/iss2/2