Overview of Medical Knowledge Inference Methods with Fusion Subgraph Structures

Corresponding author: LI Yan, 172923832@qq.com

DOI: 10.12201/bmr.202407.00038

•  

  Abstract: Objective/Significance To review the inference method of medical knowledge map with fusion subgraph structure, and to provide guidance for subsequent researchers to construct complete medical knowledge map. Method/Process By reading and analyzing relevant literature, based on knowledge graph and knowledge graph inference, the characteristics and limitations of the current knowledge inference representative model with integrated subgraph structure were analyzed, and the advantages and disadvantages of the model were compared with various knowledge inference methods in related tasks were compared, and the application status and future development prospects of such inference methods in the medical field were summarized. Results/Conclusion Future research should explore the interaction of different modal information in the medical field, so as to enrich the reasoning information to build a more complete medical knowledge map, and provide effective solutions for clinical practical problems.

  Key words: Knowledge reasoning; Subgraph structure; Graph neural networks; Knowledge graph

  Submit time: 17 July 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
• html

• 图表

• Li Xiaoying, Cai Miaozhi, Li Junlian, Ren Huiling, Ji Yujing, Deng Panpan, Xia Guanghui. Research on the construction of COVID-19 knowledge graph for literature organization. 2020. doi: 10.12201/bmr.202010.00840

  Zhao Hanqing. Knowledge reasoning and intelligent recommendation based on knowledge map of Chinese patent medicine. 2024. doi: 10.12201/bmr.202404.00018

  WU Meng, LI Jiao. Construction of multimodal perinatal health care knowledge graph towards continuing medical education. 2024. doi: 10.12201/bmr.202402.00008

  LIU Yan, Zhang Xiao-xiao, HOU Li. Research on the construction and application of academic knowledge graph for knowledge service systems. 2024. doi: 10.12201/bmr.202402.00015

  zhouyang, Kuang Zemin. Research progress，s application of medical knowledge graph. 2021. doi: 10.12201/bmr.202107.00012

  liangjing, wenyi. Research on the Application of Knowledge Graph in Medical Aided Diagnosis. 2022. doi: 10.12201/bmr.202109.00021

  WANG Huaqiong, YU Dingguo, QIAN Guiping. Construction of Multi-modal Knowledge Graph Based on Medical Social Media Data. 2022. doi: 10.12201/bmr.202209.00005

  wuhuan, hekunlun. Construction of general medical knowledge graph based on evidence-based medicine and electronic medical record data. 2024. doi: 10.12201/bmr.202409.00027

  ZHOU Hai, PENG Feiling, WEI Changfa. Research and Practice on the Construction of Syndrome Differentiation Knowledge Graph of Diagnostics of Traditional Chinese Medicine. 2020. doi: 10.12201/bmr.202004.00036

  FU Taotao, CHEN Yanmei, LI Qingna, SHAO Yiming, SU Guobin, GONG Mengchun. Construction and application of traditional Chinese medicine knowledge graph based on the Chinese Pharmacopoeia. 2024. doi: 10.12201/bmr.202407.00039

• ID	Submit time	Number	Download
  1	2024-05-21	bmr.202407.00038V1	Download

• Public  Anonymous  To author only Submit Comments