LAUSR

Bi-LSTM-CRF Network for Clinical Event Extraction With Medical Knowledge Features

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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… read more here.

Keywords: lstm crf; medical knowledge; knowledge; knowledge features ... See more keywords

Legal Text Recognition Using LSTM-CRF Deep Learning Model

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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… read more here.

Keywords: recognition; lstm crf; crf; crf model ... See more keywords

LSTM-CRF for Drug-Named Entity Recognition

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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… read more here.

Keywords: entity recognition; lstm crf; drug; drug named ... See more keywords