Purpose/Significance To propose a method of technical opportunity discovery based on dynamic graph neural network, so as to provide intelligent decision support for the innovation of atheromatosis-related technologies.Method/Process The patent data in the field of atherosclerosis from 2004 to 2024 are obtained from incoPat,the technical elements are extracted,and a dynamic technical semantic network containing the technical elements is constructed.A dynamic graph neural network model named DynGNN-TOD is proposed,and the atherosclerotic patent data are divided by sliding time window.The performance of the model is verified by comparative experiments.Result/Conclusion Experimental results show that the AUC ROC of DynGNN-TOD is 0.932 and Accuracy@10 is 62.3%,which are improved in different degrees compared with the other 3 baseline models,and can provide reliable prediction support for technical opportunity discovery.