Abstract
Artificial intelligence is widely used in the field of medical question answering. Some existing medical domain knowledge graphs have problems such as few categories of disease entities covered and small coverage of question answering. In this paper, a medical domain knowledge graph containing nearly 10,000 diseases is constructed, and a medical domain question answering system is implemented based on this knowledge graph using the Bert model. Experiment results show that the accuracy and recall of the system reach 0.96 and 0.93 respectively, with an F1 value of 0.945, which can effectively answer users' questions about the diagnosis of symptoms and medication recommendation of vast majority diseases and save medical resources to a certain extent.
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