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2
Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3213676
Abstract: Extracting clinical event expressions and their types from clinical text is a fundamental task for many applications in clinical NLP. State-of-the-art systems need handcraft features and do not take into account the representation of the…
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Keywords:
lstm crf;
medical knowledge;
knowledge;
knowledge features ... See more keywords
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2
Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/9933929
Abstract: In legal texts, named entity recognition (NER) is researched using deep learning models. First, the bidirectional (Bi)-long short-term memory (LSTM)-conditional random field (CRF) model for studying NER in legal texts is established. Second, different annotation…
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Keywords:
recognition;
lstm crf;
crf;
crf model ... See more keywords
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1
Published in 2017 at "Entropy"
DOI: 10.3390/e19060283
Abstract: Drug-Named Entity Recognition (DNER) for biomedical literature is a fundamental facilitator of Information Extraction. For this reason, the DDIExtraction2011 (DDI2011) and DDIExtraction2013 (DDI2013) challenge introduced one task aiming at recognition of drug names. State-of-the-art DNER…
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Keywords:
entity recognition;
lstm crf;
drug;
drug named ... See more keywords
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Published in 2024 at "Journal of Marine Science and Engineering"
DOI: 10.3390/jmse12091518
Abstract: NAVTEX is a key component in the Global Maritime Distress and Safety System (GMDSS) that automatically transmits urgent maritime safety information such as navigational and meteorological warnings and forecasts to vessels. For the safe navigation…
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Keywords:
navigational safety;
navtex navigational;
safety messages;
safety ... See more keywords