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

Journals

  1. Yang Y, Lin H, Yang Z, Zhang Y, Zhao D, Huai S. ADPG: Biomedical entity recognition based on Automatic Dependency Parsing Graph. Journal of Biomedical Informatics 2023;140:104317 View
  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
  3. Su F, Qian T, Zhou J, Li B, Li F, Teng C, Ji D. A tree-like structured perceptron for transition-based biomedical event extraction. Knowledge-Based Systems 2024;283:111180 View
  4. Hu J, Tang B, Lyu N, He Y, Xiong Y. CMBEE: A constraint-based multi-task learning framework for biomedical event extraction. Journal of Biomedical Informatics 2024;150:104599 View
  5. Ma S, Jiang S, Yang O, Zhang X, Fu Y, Zhang Y, Kaareen A, Ling M, Chen J, Shang C. Use of Machine Learning Tools in Evidence Synthesis of Tobacco Use Among Sexual and Gender Diverse Populations: Algorithm Development and Validation. JMIR Formative Research 2024;8:e49031 View
  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
  7. Wu P, Li X, Gu J, Qian L, Zhou G. Pipelined biomedical event extraction rivaling joint learning. Methods 2024;226:9 View