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

Data Science (268) Clinical Information and Decision Making (1404) Artificial Intelligence (1369)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48115, first published .
Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19

Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19

Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19

Authors of this article:

Zeyu Zhang1, 2 Author Orcid Image ;   Meng Fang3 Author Orcid Image ;   Rebecca Wu4 Author Orcid Image ;   Hui Zong1, 5 Author Orcid Image ;   Honglian Huang1 Author Orcid Image ;   Yuantao Tong1 Author Orcid Image ;   Yujia Xie1 Author Orcid Image ;   Shiyang Cheng1 Author Orcid Image ;   Ziyi Wei1 Author Orcid Image ;   M James C Crabbe6, 7, 8 Author Orcid Image ;   Xiaoyan Zhang1 Author Orcid Image ;   Ying Wang1, 2, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Deji Z, Tong Y, Huang H, Zhang Z, Fang M, Crabbe M, Zhang X, Wang Y. Influence of Environmental Factors and Genome Diversity on Cumulative COVID-19 Cases in the Highland Region of China: Comparative Correlational Study. Interactive Journal of Medical Research 2024;13:e43585 View
  2. Yang Y, Xu S, Hong Y, Cai Y, Tang W, Wang J, Shen B, Zong H, Yu G. Computational modeling for medical data: From data collection to knowledge discovery. The Innovation Life 2024;2(3):100079 View
  3. Guo B, Meng J, Zhao D, Jia X, Chu Y, Lin H. Integrating graph convolutional networks to enhance prompt learning for biomedical relation extraction. Journal of Biomedical Informatics 2024;157:104717 View