With the rise and rapid development of artificial intelligence，deep learning，as an important part of the field of artificial intelligence，has achieved significant results in various fields such as materials science，biomedicine，literature，and art，demonstrating high versatility and value. As an emerging deep learning method，Graph Neural Network（GNN）overcomes the limitation of traditional deep learning that can only be applied to Euclidean data frameworks，demonstrating its powerful ability to handle non-Euclidean complex data especially graph data，and demonstrating its enormous potential. Currently，GNN has been widely applied in the medical field and has been preliminarily applied in clinical and basic researches of traditional Chinese medicine. They have achieved certain results in traditional Chinese medicine prescription recommendation，symptom diagnosis and target prediction of traditional Chinese medicine. By reviewing the current application status of GNN in the field of traditional Chinese medicine and combining the characteristics of current GNN technology，it looks forward to the future development of this technology in the field of traditional Chinese medicine. It is believed that GNN has broad application prospects in clinical diagnosis，prescription treatment，traditional Chinese medicine research and utilization of classics. It is to provide ideas and inspiration for future research on Traditional Chinese Medicine based on graph neural networks so that traditional Chinese medicine can keep pace with the times，enhance intelligence and objectivity，and better serve the people's medical and health care and health cause of the motherland.