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Medical named entity recognition (NER) has wide applications in intelligent healthcare.
Simple demographics often identify people uniquely
Latanya Sweeney. 2000 · 2000
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Asif Ekbal and Sriparna Saha. 2013 · 2013
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Buzhou Tang, Hongxin Cao, Yonghui Wu, Min Jiang, and Hua Xu. 2013 · 2013
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Zhong-Yi Wang and Hong-Yu Zhang. 2013 · 2013
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Bidirectional lstm-crf models for sequence tagging
Zhiheng Huang, Wei Xu, and Kai Yu. 2015 · 2015
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Supervised named entity recognition for clinical data
Devanshu Jain. 2015 · 2015
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Cadec: A corpus of adverse drug event annotations
Sarvnaz Karimi, Alejandro Metke-Jimenez, Madonna Kemp, and Chen Wang. 2015 · 2015
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Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Richard Nock, Giorgio Patrini, Guillaume Smith, and Brian Thorne. 2017 · 2017
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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas. 2017 · 2017
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Deep active learning for named entity recognition
Yanyao Shen, Hyokun Yun, Zachary Lipton, Yakov Kronrod, and Animashree Anandkumar. 2017 · 2017
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A bidirectional lstm and conditional random fields approach to medical named entity recognition
Kai Xu, Zhanfan Zhou, Tianyong Hao, and Wenyin Liu. 2017 · 2017
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Gram-cnn: a deep learning approach with local context for named entity recognition in biomedical text
Qile Zhu, Xiaolin Li, Ana Conesa, and Cécile Pereira. 2017 · 2017
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Deep contextualized word representations
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Label-aware double transfer learning for cross-specialty medical named entity recognition
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Pd58-09 extracting structured information from pathology reports using natural language processing and machine learning
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Overview of the fourth social media mining for health (smm4h) shared tasks at acl 2019
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