Cargando…
Child-Sum EATree-LSTMs: enhanced attentive Child-Sum Tree-LSTMs for biomedical event extraction
BACKGROUND: Tree-structured neural networks have shown promise in extracting lexical representations of sentence syntactic structures, particularly in the detection of event triggers using recursive neural networks. METHODS: In this study, we introduce an attention mechanism into Child-Sum Tree-LSTM...
Autores principales: | Wang, Lei, Cao, Han, Yuan, Liu, Guo, Xiaoxu, Cui, Yachao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10268412/ https://www.ncbi.nlm.nih.gov/pubmed/37322443 http://dx.doi.org/10.1186/s12859-023-05336-7 |
Ejemplares similares
-
Identifying geopolitical event precursors using attention-based LSTMs
por: Hossain, K. S. M. Tozammel, et al.
Publicado: (2022) -
Forecasting Hazard Level of Air Pollutants Using LSTM’s
por: Gul, Saba, et al.
Publicado: (2020) -
Generalised Analog LSTMs Recurrent Modules for Neural Computing
por: Adam, Kazybek, et al.
Publicado: (2021) -
Anomaly Detection Using an Ensemble of Multi-Point LSTMs
por: Lee, Geonseok, et al.
Publicado: (2023) -
Vehicle Trajectory Prediction with Lane Stream Attention-Based LSTMs and Road Geometry Linearization
por: Yu, Dongyeon, et al.
Publicado: (2021)