Nowadays, a large amount of medical domain knowledge on the Internet can be used for medical diagnosis, but traditional search engines cannot make reasonable judgments based on the actual situation of patients and fail to meet the needs of use. Therefore, this study mainly develops a question-answering system based on a knowledge graph. The system is applied to the medical field, which uses crawler technology to obtain a large amount of medical data and stores them in the constructed medical knowledge graph of the Neo4j graph database. At the same time, in order to enable the system to further understand the user’s medical questions, this study proposes methods based on BERT and BERT-BiLSTM-CRF models for identifying intent information and entity information in questions, respectively. Finally, the system uses the intent and entity information to make a query in the knowledge graph and provides users with appropriate answers, thus completing the construction of a medical question-answering system