The Model for Pneumothorax Knowledge Extraction Based on Dependency Syntactic Analysis

Xiangge Liu (), Jing Li () and Yuzhuo Zhao ()
Additional contact information
Xiangge Liu: Beijing Jiaotong University
Jing Li: Beijing Jiaotong University
Yuzhuo Zhao: Chinese PLA General Hospital

A chapter in LISS 2021, 2022, pp 160-168 from Springer

Abstract: Abstract As the frontier application technology of artificial intelligence in the medical field, medical knowledge mapping plays an important role in assisting medical staff in the diagnosis and treatment of diseases. In this paper, pneumothorax is selected as the research object, and the method of natural language processing is applied to study the knowledge extraction model involved in the construction of knowledge map. Firstly, based on the principle of dependency syntax, the grammatical relationship of pneumothorax corpus is analyzed, and the dependency syntax tree is constructed. Secondly, based on the special text features of pneumothorax corpus, a knowledge extraction model based on Text Syntactic Structure and dependency representation is proposed, and the predicate is used as the core term to extract pneumothorax triples. Finally, based on the standardized knowledge representation defined by experts, the automatically extracted triples are normalized and presented in the form of pneumothorax knowledge map.

Keywords: Knowledge graph; Knowledge extraction; Dependency syntactic analysis; Pneumothorax (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-16-8656-6_15

Ordering information: This item can be ordered from
http://www.springer.com/9789811686566

DOI: 10.1007/978-981-16-8656-6_15

Access Statistics for this chapter

More chapters in Lecture Notes in Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().