Objective To explore the contribution of symptoms to syndromes of chronic obstructive pulmonary disease acute exacerbation based on Bayesian network and construct the association mode of symptoms and phlegmheat congesting lung syndrome. Methods Phlegm-heat congesting lung syndrome database was built adopting 1768 patients’ data researched in 9 national provincial Chinese medicine hospitals for 2 years. Data were imported in Bayesian network after preprocessing. Taking phlegm-heat congesting lung syndrome as the target variable

taking the variables selected from the results of the decision tree as the input variables

Bayesian network algorithm was carried out by IBM SPSS Modeler 14. 2 software. Comparing analysis was made on the results gained from TAN and markov blanket models using assessment and analysis. Results Phlegm-heat congesting lung syndrome causality showed below.First

Yellow phlegm

white sticky phlegm

slippery-rapid pulse

rapid pulse

constipation

thirst and liking cold drink. Second

Yellow phlegm

white sticky phlegm

slippery-rapid pulse and yellow greasy fur. Third

Yellow phlegm

white sticky phlegm

slippery-rapid pulse

yellow fur and yellow greasy fur. Forth

Yellow phlegm

white sticky phlegm

slippery-rapid pulse and red tongue. In the above 4 items

the common symptoms were yellow phlegm

white sticky phlegm and slippery-rapid pulse. Among them

yellow phlegm made the most contribution

0. 72. White sticky phlegm was the second

0. 61. Markov blanket model showed that the contribution of thirst and liking cold drink

constipation and yellow greasy fur to phlegm-heat congesting lung syndrome was more than 0. 7.Conclusion There were 4 items of causality between phlegm-heat congesting lung syndrome and symptoms. Yellow phlegm

thirst and liking cold drink

constipation and yellow greasy fur made great contributions to phlegm-heat congesting lung syndrome.