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Relation Extraction
This chapter introduces methods for extracting the relations between entities mentioned in electronic health records, scientific literature, reports,...
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Contrast with major classifier vectors for federated medical relation extraction with heterogeneous label distribution
Federated medical relation extraction enables multiple clients to train a deep network collaboratively without sharing their raw medical data. To...
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Medical Causality Extraction: A Two-Stage Based Nested Relation Extraction Model
The extraction of medical causality contributes to constructing medical causal knowledge graphs, and enhancing the interpretability of modern medical...
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Chapter-Level Stepwise Temporal Relation Extraction Based on Event Information for Chinese Clinical Medical Texts
Temporal relation extraction of medical events for Chinese clinical medical texts is an important natural language processing task, which is the...
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Domain Robust Pipeline for Medical Causal Entity and Relation Extraction Task
Medical entity and relation extraction is an essential task for medical knowledge graph, which can provide explanatory answers for medical search...
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Multi-head Attention and Graph Convolutional Networks with Regularized Dropout for Biomedical Relation Extraction
Automatic extraction of biomedical relation from text becomes critical because manual relation extraction requires significant time and resources....
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Enhancing Relation Extraction from Biomedical Texts by Large Language Models
In this study, we propose a novel relation extraction method enhanced by large language models (LLMs). We incorporated three relation extraction...
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Combining Biaffine Model and Constraints Inference for Chinese Clinical Temporal Relation Extraction
The extraction of clinical events and their temporal relation from electronic medical records (EMRs) is crucial and plays a significant role in the...
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Span-based joint entity and relation extraction augmented with sequence tagging mechanism
Span-based joint extraction simultaneously conducts named entity recognition (NER) and relation extraction (RE) in a text span form. However, since...
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A BART-Based Study of Entity-Relationship Extraction for Electronic Medical Records of Cardiovascular Diseases
With the advancement of training techniques, models such as BERT and GPT have been pre-trained on massive unlabeled texts, enabling effective...
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Temporal Relation Extraction from Clinical Texts Using Knowledge Graphs
An integral task for many natural language processing applications is the extraction of the narrative process described in a document. For...
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Hybrid Granularity-Based Medical Event Extraction in Chinese Electronic Medical Records
Chinese medical event extraction (CMEE) has risen the attention of a large amount of researchers. The event extraction in Chinese electronic medical...
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Relation extraction: advancements through deep learning and entity-related features
Capturing semantics and structure surrounding the target entity pair is crucial for relation extraction. The task is challenging due to the limited...
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Joint Model for End-to-End Relation Extraction
In this chapter, we propose a new approach which combines Neural Networks and Markov Logic Networks to address all the three sub-tasks of end-to-end...
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Joint relational triple extraction based on potential relation detection and conditional entity map**
Joint relational triple extraction treats entity recognition and relation extraction as a joint task to extract relational triples, and this is a...
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Medical Decision Tree Extraction: A Prompt Based Dual Contrastive Learning Method
The extraction of decision-making knowledge in the form of decision trees from unstructured textual knowledge sources is a novel research area within...
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Dynamic Multi-View Fusion Mechanism for Chinese Relation Extraction
Recently, many studies incorporate external knowledge into character-level feature based models to improve the performance of Chinese relation...
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Multi-task learning for few-shot biomedical relation extraction
Artificial intelligence (AI) has advanced rapidly, but it has limited impact on biomedical text understanding due to a lack of annotated datasets...
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LLM Collaboration PLM Improves Critical Information Extraction Tasks in Medical Articles
With the development of modern medical informatics and databases, medical professionals are increasingly inclined to use evidence-based medicine to...
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Information extraction from electronic medical documents: state of the art and future research directions
In the medical field, a doctor must have a comprehensive knowledge by reading and writing narrative documents, and he is responsible for every...
