医学知识图谱构建技术与研究进展

医学知识图谱是实现智慧医疗的基石，有望带来更高效精准的医疗服务。然而，现有知识图谱构建技术在医学领域中普遍存在效率低，限制多，拓展性差等问题。针对医疗数据跨语种，专业性强，结构复杂等特点，对构建医学知识图谱的关键技术进行了自底向上的全面解析，涵盖了医学知识表示、抽取、融合和推理以及质量评估五部分内容。此外，还介绍了医学知识图谱在信息检索、知识问答、智能诊断等医疗服务中的应用现状。最后，结合当前医学知识图谱构建技术面临的重大挑战和关键问题，对其发展前景进行了展望。

The Construction Techniques and Research Development of Medical Knowledge Graph

Medical knowledge graph is the cornerstone of Artificial Intelligence and Smart Healthcare, and leading to more efficient and accurate medical service. However, current constructing techniques of knowledge graph have some common defects in efficiency, scalability and applicability. Considering the specific features of medical data, this paper analyzes and classifies the key techniques and methods involved in the construction of medical knowledge graph in a bottom-up way, including representation, extraction, fusion and reasoning of medical knowledge and quality assessment of medical knowledge graph. Furthermore, the paper also introduces the research and application of search engine, question-answering system and decision support system based on medical knowledge graph. Finally, the paper summarizes challenges and major problems of medical knowledge graph, and prospects for future development.