This paper is in the following e-collection/theme issue:

Data Science (270) Pharmacovigilance (134) Depression and Mood Disorders; Suicide Prevention (1363) Natural Language Processing (693) Clinical Information and Decision Making (1407) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (156) Ontologies, Classifications, and Coding (239) Machine Learning (1465)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41100, first published .
Supervised Relation Extraction Between Suicide-Related Entities and Drugs: Development and Usability Study of an Annotated PubMed Corpus

Supervised Relation Extraction Between Suicide-Related Entities and Drugs: Development and Usability Study of an Annotated PubMed Corpus

Supervised Relation Extraction Between Suicide-Related Entities and Drugs: Development and Usability Study of an Annotated PubMed Corpus

Authors of this article:

Karina Karapetian1 Author Orcid Image ;   Soo Min Jeon2 Author Orcid Image ;   Jin-Won Kwon3 Author Orcid Image ;   Young-Kyoon Suh1 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Karina Karapetian   1 * , MS ;   Soo Min Jeon   2 * , PharmD, PhD ;   Jin-Won Kwon   3 , PhD ;   Young-Kyoon Suh   1 , PhD

1 School of Computer Science and Engineering, Kyungpook National University, Daegu, Republic of Korea

2 College of Pharmacy, Jeju National University, Jeju, Republic of Korea

3 BK21 FOUR Community-Based Intelligent Novel Drug Discovery Education Unit, College of Pharmacy and Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Young-Kyoon Suh, PhD
  • School of Computer Science and Engineering
  • Kyungpook National University
  • Rm. 520, IT-5
  • 80 Daehak-ro, Bukgu
  • Daegu, 41566
  • Republic of Korea
  • Phone: 82 53 950 6372
  • Email: yksuh@knu.ac.kr