Ontology-Based Healthcare Named Entity Recognition from Twitter Messages Using a Recurrent Neural Network Approach
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References listed on IDEAS
- Amir Karami & London S. Bennett & Xiaoyun He, 2018. "Mining Public Opinion about Economic Issues: Twitter and the U.S. Presidential Election," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 9(1), pages 18-28, January.
- Meijing Li & Tsendsuren Munkhdalai & Xiuming Yu & Keun Ho Ryu, 2015. "A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-10, October.
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- Khishigsuren Davagdorj & Ling Wang & Meijing Li & Van-Huy Pham & Keun Ho Ryu & Nipon Theera-Umpon, 2022. "Discovering Thematically Coherent Biomedical Documents Using Contextualized Bidirectional Encoder Representations from Transformers-Based Clustering," IJERPH, MDPI, vol. 19(10), pages 1-21, May.
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Keywords
named entity recognition; healthcare; deep learning; recurrent neural network; word embedding; ontology; unified medical language system; conditional random field; Twitter;All these keywords.
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