Drug Target Extraction from Biomedical Articles Based on a Two-Stage Cascading Framework

Xuesi Li, Liangping Ding, Zhixiong Zhang*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Automatic access to drug target in biomedical articles is crucial for drug innovation. Determining a drug target requires specific context, which is usually expressed as a certain sentence. Thus, this study develops a two-stage cascading framework for extracting drug target from biomedical article, in which drug target sentences are identified first and then passed to the second stage to identify the drug target entity. The experiments show that our method could be a feasible way to automatically extract drug target knowledge from biomedical articles.

Original languageEnglish
Title of host publicationProceedings of the ACM/IEEE Joint Conference on Digital Libraries
PublisherIEEE
Pages245-246
Number of pages2
ISBN (Electronic)9798350399318
ISBN (Print)9798350399318
DOIs
Publication statusPublished - 3 Oct 2023
Event2023 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2023 - Santa Fe, United States
Duration: 26 Jun 202330 Jun 2023

Publication series

NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries
Volume2023-June
ISSN (Print)1552-5996

Conference

Conference2023 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2023
Country/TerritoryUnited States
CitySanta Fe
Period26/06/2330/06/23

Keywords

  • drug target extraction
  • sequence labeling
  • text classification

Research Beacons, Institutes and Platforms

  • Manchester Institute of Innovation Research

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