Joint extraction of entity and relation based on fine-tuning BERT for long biomedical literatures
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a novel joint entity and relation extraction model for biomedical literature. The advanced deep learning approach enhances accuracy and robustness in knowledge graph construction.
Area Of Science
- Biomedical Informatics
- Natural Language Processing
- Artificial Intelligence
Background
- The rapid growth of biomedical literature necessitates efficient information extraction methods.
- Automating the extraction of entities and relations is crucial for advancing biomedical research.
- Existing methods struggle with long-distance dependencies in extensive scientific texts.
Purpose Of The Study
- To develop a joint extraction model for entities and relations from biomedical literature.
- To address challenges of intra-sentence and cross-sentence extraction, and long-distance information dependence.
- To improve the accuracy and robustness of information extraction in the biomedical domain.
Main Methods
- Utilized a fine-tuning BERT text classification pre-training model.
- Incorporated Graph Convolutional Network (GCN) learning.
- Implemented Robust Learning Against Textual Label Noise with Self-Mixup Training.
- Employed Local Regularization Conditional Random Fields (CRFs).
Main Results
- The model effectively identifies entities in complex biomedical texts.
- Achieved successful extraction of triples both within and across sentences.
- Demonstrated reduced impact of noisy data during training.
- Showcased improved model robustness and accuracy on benchmark datasets.
- Enabled precise large language model-enhanced knowledge graph construction for biomedical tasks.
Conclusions
- The proposed joint extraction model significantly enhances information extraction from biomedical literature.
- The model's integration of advanced deep learning techniques leads to superior performance.
- The developed model facilitates more accurate and robust biomedical knowledge graph construction.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
Knowledge of anatomy is essential to understand human biology and medicine. Anatomists and health care professionals use standard terminology to describe the human body with more precision and no ambiguity. Anatomical terms have mostly Greek and Latin-derived roots. Because these languages are rarely used in conversation, the meaning of words remains the same. Each term is made up of a root in between the prefixes and suffixes. The root of a term often refers to an organ, tissue, or condition,...
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor.
Empathy is often confused with pity and sympathy, which are different reactions to the situation of someone else or...
Tissue transplantation is a significant medical procedure involving the transfer of cells, tissues, or organs from a donor to a recipient, with the primary aim of restoring lost functions. This procedure is crucial in treating a broad spectrum of diseases, including kidney diseases, liver failure, heart disease, and certain types of cancers.
The Biology of Tissue Transplantation
The biology of tissue transplantation hinges on the Major Histocompatibility Complex (MHC) molecules. These molecules...