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

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Natural Language Processing (706)

Published on in Vol 10, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37804, first published .
Conditional Probability Joint Extraction of Nested Biomedical Events: Design of a Unified Extraction Framework Based on Neural Networks

Conditional Probability Joint Extraction of Nested Biomedical Events: Design of a Unified Extraction Framework Based on Neural Networks

Conditional Probability Joint Extraction of Nested Biomedical Events: Design of a Unified Extraction Framework Based on Neural Networks

Authors of this article:

Yan Wang1 Author Orcid Image ;   Jian Wang1 Author Orcid Image ;   Huiyi Lu2 Author Orcid Image ;   Bing Xu2 Author Orcid Image ;   Yijia Zhang3 Author Orcid Image ;   Santosh Kumar Banbhrani1 Author Orcid Image ;   Hongfei Lin1 Author Orcid Image
Article Authors Cited by (11) Tweetations (3) Metrics

Journals

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  2. Wang L, Cao H, Yuan L, Guo X, Cui Y. Child-Sum EATree-LSTMs: enhanced attentive Child-Sum Tree-LSTMs for biomedical event extraction. BMC Bioinformatics 2023;24(1) View
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  6. Wang L, Cao H, Yuan L. Child-Sum (N2E2N)Tree-LSTMs: An interactive Child-Sum Tree-LSTMs to extract biomedical event. Systems and Soft Computing 2024;6:200075 View
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  10. Su F, Teng C, Li F, Li B, Zhou J, Ji D. Generative Biomedical Event Extraction With Constrained Decoding Strategy. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2024;21(6):2471 View

Books/Policy Documents

  1. Chen G, Wu P, Gu J, Qian L, Zhou G. Natural Language Processing and Chinese Computing. View