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

Data Science (357) Pharmacovigilance (171) Depression and Mood Disorders; Suicide Prevention (1691) Natural Language Processing (917) Clinical Information and Decision Making (1916) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (215) Ontologies, Classifications, and Coding (324) Machine Learning (2077)

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 (3) Tweetations (4) Metrics

Journals

  1. Arowosegbe A, Oyelade T. Suicide Risk Assessment and Prevention Tools in the UK: Current Landscape and Future Directions. Psychiatry International 2023;4(4):354 View
  2. Holmes G, Tang B, Gupta S, Venkatesh S, Christensen H, Whitton A. Applications of Large Language Models in the Field of Suicide Prevention: Scoping Review. Journal of Medical Internet Research 2025;27:e63126 View

Conference Proceedings

  1. Tiwari S, Goyal H, adnan M, Shrivastava A, Yadav K, Rao A. 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE). Clinical Text Analysis with Natural Language Processing: A BERT-based Approach View