PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 10, 2026Tsinghua Science & Technology0 citationsOpen Access

CRE-RFGP: Relation Extraction for Chinese Medical Records

View Full Paper
Ask AI
Bookmark
Share

Authors

QQQijie QianXXXin XuBLBo Li

Discussion

Loading...

Member takes

Overview

This approach improves entity and relation extraction in Chinese medical records, enhancing diagnostic applications.

Key Points

  • The aim is to improve the extraction of relations and entities from Chinese medical records to construct effective knowledge graphs.
  • Proposes a novel relation extraction method called CRE-RFGP.
  • Utilizes a relation-first decoder for predicting and filtering relations.
  • Employs a global pointer network for identifying and handling nested entities.
  • Introduces an entity correspondence matrix for aligning subjects, objects, and their relations into triples.
  • Achieves leading performance compared to six state-of-the-art approaches in relation extraction.
  • Improvements in precision of extracted triples due to reduced complexity.
  • Effectively handles overlapping subjects and objects in sentences, improving extraction accuracy.

Cite This Study

Qian et al. (2026) studied this question.

synapsesocial.com/papers/69d894326c1944d70ce05174https://doi.org/10.26599/tst.2025.9010075
View Full Paper
Ask AI
Bookmark
Share