Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (21): 14-23.DOI: 10.3778/j.issn.1002-8331.2103-0469

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Review of Deep Learning-Based Biomedical Entity Relation Extraction Research

WEI Hao, ZHOU Ai, ZHANG Yijia, CHEN Fei, QU Wen, LU Mingyu   

  1. School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning 116026, China
  • Online:2021-11-01 Published:2021-11-04



  1. 大连海事大学 信息科学技术学院,辽宁 大连 116026


With the development of life science and technology, the literature in the field of biomedicine has grown exponentially. How to excavate and extract valuable information from massive literature has become a new research opportunity in the field of biomedicine. As the core technology of information extraction, named entity recognition and relationship extraction become the basis and key of biomedical text mining. Its main work is to identify the entities in the biomedical text and extract the biomedical semantic relations between the entities. This paper aims to summarize the deep learning-based methods of entity identification and relationship extraction in biomedical field. It comprehensively expounds the development process of various technologies from the perspectives of concept, progress and status quo, and further clarifies the exploration direction of biomedical text information extraction.

Key words: biomedical, information extraction, named entity recognition, relation extraction, deep learning



关键词: 生物医学, 信息抽取, 命名实体识别, 关系抽取, 深度学习