Technology Center of Software Engineering, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China;University of Chinese Academy of Sciences, Beijing 100049, China 在期刊界中查找 在百度中查找 在本站中查找
Diversified expression of medical information and inefficient utilization of medical knowledge are encountered in online consultations. This study designs and implements an interactive intelligent diagnosis guidance system based on medical knowledge graphs. The system introduces medical knowledge graphs to provide medical knowledge and relies on entity recognition and entity linking technology to standardize the medical expression in the main condition description text. Moreover, it uses the medical entity to generate knowledge subgraphs and obtain their semantic information and merges the semantic information of the subgraphs and patient condition description to obtain department confidence. When the confidence of the recommended department is low, multi-round interactive inquiry can supplement the patient’s symptom information, and finally, the recommended department is determined. The system can provide technical support for building a fast and accurate intelligent medical system to improve the efficiency of diagnosis and alleviate the shortage of medical resources.
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