Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications

IF 7.7 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Big Data Mining and Analytics Pub Date : 2023-01-26 DOI:10.26599/BDMA.2022.9020021

Xuehong Wu;Junwen Duan;Yi Pan;Min Li

引用次数: 13

Abstract

Medical knowledge graphs (MKGs) are the basis for intelligent health care, and they have been in use in a variety of intelligent medical applications. Thus, understanding the research and application development of MKGs will be crucial for future relevant research in the biomedical field. To this end, we offer an in-depth review of MKG in this work. Our research begins with the examination of four types of medical information sources, knowledge graph creation methodologies, and six major themes for MKG development. Furthermore, three popular models of reasoning from the viewpoint of knowledge reasoning are discussed. A reasoning implementation path (RIP) is proposed as a means of expressing the reasoning procedures for MKG. In addition, we explore intelligent medical applications based on RIP and MKG and classify them into nine major types. Finally, we summarize the current state of MKG research based on more than 130 publications and future challenges and opportunities.

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医学知识图谱：数据源、构建、推理与应用

医学知识图是智能医疗的基础，已在各种智能医疗应用中得到应用。因此，了解MKG的研究和应用发展将对未来生物医学领域的相关研究至关重要。为此，我们在这项工作中对MKG进行了深入的回顾。我们的研究从四种类型的医学信息源、知识图创建方法和MKG开发的六个主要主题开始。此外，从知识推理的角度讨论了三种流行的推理模型。提出了一种推理实现路径（RIP）来表示MKG的推理过程。此外，我们探索了基于RIP和MKG的智能医疗应用，并将其分为九大类型。最后，我们根据130多篇出版物总结了MKG研究的现状以及未来的挑战和机遇。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data Mining and Analytics Computer Science-Computer Science Applications

CiteScore

20.90

自引率

2.20%

发文量

期刊介绍： Big Data Mining and Analytics, a publication by Tsinghua University Press, presents groundbreaking research in the field of big data research and its applications. This comprehensive book delves into the exploration and analysis of vast amounts of data from diverse sources to uncover hidden patterns, correlations, insights, and knowledge. Featuring the latest developments, research issues, and solutions, this book offers valuable insights into the world of big data. It provides a deep understanding of data mining techniques, data analytics, and their practical applications. Big Data Mining and Analytics has gained significant recognition and is indexed and abstracted in esteemed platforms such as ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ, CNKI, and more. With its wealth of information and its ability to transform the way we perceive and utilize data, this book is a must-read for researchers, professionals, and anyone interested in the field of big data analytics.