Deep Convolutional Neural Network Diabetic Entity Relationship Extraction Model Based on Enhanced Semantic Representation
Tao Yu, Cuo Yong · 2021
Diabetes, as the number one chronic disease in China, plagues the lives of people of different age groups and causes great distress to people. This paper extracts the semantic relationships among diabetes entities through the entity relationship extraction technique, which helps to build the knowledge graph of diabetes domain. The experimental results show that the deep convolutional neural network (ESPDCNN) based on enhanced semantic representation proposed in this paper effectively improves the accuracy of the diabetic entity relationship extraction model.