Objectives : One of the crucial combinations of acupoints for treating various disorders involves the Eight Confluent acupoints. The present study aims to investigate the selection patterns of the Eight Confluent acupoints in clinical trials and determine the most frequent pairings through network analysis. Methods : The frequencies of the Eight Confluent acupoints were extracted from the Acusynth database, which includes data from 421 clinical investigations. We examined the degree distribution, eigenvector centrality, proximity centrality, and betweenness centrality of these acupoint combinations using network analysis. Results : Data mining revealed that among the Eight Confluent acupoints, PC6 and TE5 were the most commonly applied in the treatment of 30 disorders. Additionally, we identified the most frequently co-occurring pairs of Eight Confluent acupoints by network analysis which included PC6-GV20, SP4-GV4, LU7-LI4, TE5-PC7, GB41-SP6, KI6-BL62, and SI3-BL62. Conclusions : Through the application of data mining and network analysis, we have elucidated the selection patterns and combinations of the Eight Confluent acupoints. These findings provide valuable insights that can enhance doctors' understanding of clinical databasedriven Eight Confluent acupoint selection patterns.