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

Machine Learning (1465) Natural Language Processing (693) Decision Support for Health Professionals (1186) Clinical Informatics (1022)

Published on in Vol 10, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41136, first published .
Relation Extraction in Biomedical Texts Based on Multi-Head Attention Model With Syntactic Dependency Feature: Modeling Study

Relation Extraction in Biomedical Texts Based on Multi-Head Attention Model With Syntactic Dependency Feature: Modeling Study

Relation Extraction in Biomedical Texts Based on Multi-Head Attention Model With Syntactic Dependency Feature: Modeling Study

Authors of this article:

Yongbin Li1 Author Orcid Image ;   Linhu Hui1 Author Orcid Image ;   Liping Zou1 Author Orcid Image ;   Huyang Li1 Author Orcid Image ;   Luo Xu1 Author Orcid Image ;   Xiaohua Wang1 Author Orcid Image ;   Stephanie Chua2 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

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  2. Crema C, Buonocore T, Fostinelli S, Parimbelli E, Verde F, Fundarò C, Manera M, Ramusino M, Capelli M, Costa A, Binetti G, Bellazzi R, Redolfi A. Advancing Italian biomedical information extraction with transformers-based models: Methodological insights and multicenter practical application. Journal of Biomedical Informatics 2023;148:104557 View
  3. Sosa D, Neculae G, Fauqueur J, Altman R. Elucidating the semantics-topology trade-off for knowledge inference-based pharmacological discovery. Journal of Biomedical Semantics 2024;15(1) View
  4. Li Y, Luan Z, Liu Y, Liu H, Qi J, Han D. Automated information extraction model enhancing traditional Chinese medicine RCT evidence extraction (Evi-BERT): algorithm development and validation. Frontiers in Artificial Intelligence 2024;7 View