Research on Intelligent Diagnosis Model Based on the Medical Knowledeg Graph of Multi-source Data Fusion

Aiming at the problem of the shortage of online medical resources caused by the surge in the amount of online medical consultation and the ineffective use of a large amount of medical data, this paper proposes a comprehensive online intelligent consultation program. First, obtain heterogeneous data sources through multiple channels, use deep learning technology to build a medical knowledge graph, and store it as a knowledge repository then build an intelligent automatic consultation model and medical knowledge retrieval query model, use natural language processing technology to parse semantics for the question of users, and the answer is retrieved in the medical knowledge repository through the semantic query logic conversion, and finally an intelligent questioning model based on the medical knowledge graph covering the whole disease is implemented. This solution can not only meet the needs of patients for online consultation, reduce the workload of medical staff, but also provide clinical decision support services, improve the accuracy of intelligent diagnosis, and reduce the inaccuracy rate of expert decision-making and the cost of consultation.