Inter-sentence relation extraction with document-level graph convolutional neural network
Inter-sentence relation extraction deals with a number of complex semantic relationships in
documents, which require local, non-local, syntactic and semantic dependencies. Existing …
documents, which require local, non-local, syntactic and semantic dependencies. Existing …
[HTML][HTML] A neural joint model for entity and relation extraction from biomedical text
Extracting biomedical entities and their relations from text has important applications on
biomedical research. Previous work primarily utilized feature-based pipeline models to …
biomedical research. Previous work primarily utilized feature-based pipeline models to …
[HTML][HTML] Fine-tuning bidirectional encoder representations from transformers (BERT)–based models on large-scale electronic health record notes: an empirical study
Background: The bidirectional encoder representations from transformers (BERT) model has
achieved great success in many natural language processing (NLP) tasks, such as named …
achieved great success in many natural language processing (NLP) tasks, such as named …
Biomedical entity representations with synonym marginalization
Biomedical named entities often play important roles in many biomedical text mining tools.
However, due to the incompleteness of provided synonyms and numerous variations in their …
However, due to the incompleteness of provided synonyms and numerous variations in their …
Text mining for drug discovery
S Zheng, S Dharssi, M Wu, J Li, Z Lu - Bioinformatics and Drug Discovery, 2019 - Springer
Recent advances in technology have led to the exponential growth of scientific literature in
biomedical sciences. This rapid increase in information has surpassed the threshold for …
biomedical sciences. This rapid increase in information has surpassed the threshold for …
MetaMap Lite: an evaluation of a new Java implementation of MetaMap
D Demner-Fushman, WJ Rogers… - Journal of the American …, 2017 - academic.oup.com
MetaMap is a widely used named entity recognition tool that identifies concepts from the
Unified Medical Language System Metathesaurus in text. This study presents MetaMap Lite …
Unified Medical Language System Metathesaurus in text. This study presents MetaMap Lite …
[HTML][HTML] Broad-coverage biomedical relation extraction with SemRep
Background In the era of information overload, natural language processing (NLP)
techniques are increasingly needed to support advanced biomedical information …
techniques are increasingly needed to support advanced biomedical information …
Document-level relation extraction with dual-tier heterogeneous graph
Document-level relation extraction (RE) poses new challenges over its sentence-level
counterpart since it requires an adequate comprehension of the whole document and the …
counterpart since it requires an adequate comprehension of the whole document and the …
Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting
Objective To develop a natural language processing system that identifies relations of
medications with adverse drug events from clinical narratives. This project is part of the 2018 …
medications with adverse drug events from clinical narratives. This project is part of the 2018 …
Chemical-induced disease relation extraction via convolutional neural network
This article describes our work on the BioCreative-V chemical–disease relation (CDR)
extraction task, which employed a maximum entropy (ME) model and a convolutional neural …
extraction task, which employed a maximum entropy (ME) model and a convolutional neural …