基于知识图谱的医学决策支持应用综述

A Review of Medical Decision Supports Based on Knowledge Graph

【目的】对知识图谱推理在医学决策支持中的应用进行系统综述,为类似跨领域研究提供思路。【文献范围】总计纳入参考文献39篇,其中知识图谱推理文献多来源于计算机会议,其他文献多以"知识图谱推理"和"医学决策支持"为关键字从Web of Science数据库筛选得到。【方法】回顾医学决策支持发展历程,从传统医学到循证医学,再到计算机和医学知识图谱辅助的临床决策支持系统,其中医学知识图谱和知识图谱推理是实现以上发展转变的关键工具。【结果】医学知识图谱与先进的知识图谱推理方法的结合可以极大地减轻临床医生的诊断压力,提高诊断效率,甚至减少误诊率。【局限】以综述为主,没有对模型进行深入解析。【结论】医学知识图谱就像是临床决策支持系统的大脑,而知识图谱推理则教会大脑如何运用这些知识。需要更为完整和准确的全科医学知识图谱,并不断改进知识图谱推理算法。

[Objective] This paper systematically reviews the supporting applications for medical decisions based on knowledge graphs, aiming to expand similar interdisciplinary research. [Coverage] A total of 39 articles were retrieved from computer science conferences, as well as Web of Science with keywords of "knowledge graph reasoning" and "medical decision support". [Methods] We reviewed the developments of medical decision support, from the perspectives of traditional and evidence-based medicine, as well as the computer and knowledge graph assisted systems. [Results] The medicine knowledge graph and reasoning significantly changed medical decision support systems, which also alleviated stress facing physicians, improved diagnosis efficiency, and reduced misdiagnosis. [Limitations] This article did not provide in-depth analysis of the reviewed models.[Conclusions] Medical knowledge graph is the "brain" of clinical decision support system, and knowledge graph reasoning helps the brain utilize relevant knowledge. We need to construct more comprehensive medical knowledge graphs, and improve their reasoning algorithms.