Application of machine learning methods in prediction of the body constitution types and transformation trends of traditional Chinese medicine: from the datasets of questionnaire survey on elderly people in Southwest China

This study establishes the first machine learning framework to effectively predict the dynamic evolution of TCM constitution. Our findings show that SVM excels at predicting specific future states, while RFC is more adept at capturing overall evolutionary trends. This framework provides a novel quantitative tool for advancing proactive health management aligned with the TCM principle of "Zhi Wei Bing". The models' inability to reliably predict constitutional deterioration highlights the critical need to incorporate multi-modal data to capture complex pathophysiological mechanisms in future research.