Dictionary-based matching graph network for biomedical named entity recognition [PDF]
Scientific Reports, 2023 Biomedical named entity recognition (BioNER) is an essential task in biomedical information analysis. Recently, deep neural approaches have become widely utilized for BioNER.
Yinxia Lou, Xun Zhu, Kai Tan
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Hierarchical shared transfer learning for biomedical named entity recognition [PDF]
BMC Bioinformatics, 2022 Background Biomedical named entity recognition (BioNER) is a basic and important medical information extraction task to extract medical entities with special meaning from medical texts.
Zhaoying Chai +5 more
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Leveraging network analysis to evaluate biomedical named entity recognition tools [PDF]
Scientific Reports, 2021 The ever-growing availability of biomedical text sources has resulted in a boost in clinical studies based on their exploitation. Biomedical named-entity recognition (bio-NER) techniques have evolved remarkably in recent years and their application in ...
Eduardo P. García del Valle +5 more
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NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding [PDF]
npj Systems Biology and Applications, 2021 Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing biomedical documents. Over the last two decades1,2, the most dramatic advances in MR have followed in the wake of critical corpus development3.
Kanix Wang +24 more
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Enhancing biomedical named entity recognition with parallel boundary detection and category classification [PDF]
BMC BioinformaticsBackground Named entity recognition is a fundamental task in natural language processing. Recognizing entities in biomedical text, known as the BioNER, is particularly crucial for cutting-edge applications.
Yu Wang +4 more
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Exploring the effects of drug, disease, and protein dependencies on biomedical named entity recognition: A comparative analysis [PDF]
Frontiers in Pharmacology, 2022 Background: Biomedical named entity recognition is one of the important tasks of biomedical literature mining. With the development of natural language processing technology, many deep learning models are used to extract valuable information from the ...
Peifu Han +5 more
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A pre-training and self-training approach for biomedical named entity recognition. [PDF]
PLoS ONE, 2021 Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts of labeled training data in
Shang Gao +3 more
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Improving deep learning method for biomedical named entity recognition by using entity definition information [PDF]
BMC Bioinformatics, 2021 Background Biomedical named entity recognition (NER) is a fundamental task of biomedical text mining that finds the boundaries of entity mentions in biomedical text and determines their entity type.
Ying Xiong +6 more
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A Boundary Assembling Method for Nested Biomedical Named Entity Recognition
IEEE Access, 2020 Biomedical named entity recognition (BNER) is an important task in biomedical natural language processing, in which neologisms (new terms, words) are coined constantly.
Yanping Chen +7 more
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Comparing general and specialized word embeddings for biomedical named entity recognition [PDF]
PeerJ Computer Science, 2021 Increased interest in the use of word embeddings, such as word representation, for biomedical named entity recognition (BioNER) has highlighted the need for evaluations that aid in selecting the best word embedding to be used.
Rigo E. Ramos-Vargas +2 more
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