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We curated WikiPII, an automatically labeled dataset composed of Wikipedia biography pages, annotated for personal information extraction.
Extracting umls concepts from medical text using general and domain-specific deep learning models
Kathleen C Fraser, Isar Nejadgholi, Berry De Bruijn, Muqun Li, Astha LaPlante, and Khaldoun Zine El Abidine. 2019 · 1910
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MUC-5 evaluation metrics
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IREX project overview
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Introduction to the conll-2003 shared task: Language-independent named entity recognition
Erik F Sang and Fien De Meulder. 2003 · 2003
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Scanning electronic documents for personally identifiable information
Tuomas Aura, Thomas A Kuhn, and Michael Roe. 2006 · 2006
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Various criteria in the evaluation of biomedical named entity recognition
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Named entity recognition in machine anonymization
Filip Graliński, Krzysztof Jassem, Michał Marcińczuk, and Paweł Wawrzyniak. 2009 · 2009
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Design challenges and misconceptions in named entity recognition
Lev Retinov and Dan Roth. 2009 · 2009
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Strategies for de-identification and anonymization of electronic health record data for use in multicenter research studies
Clete A Kushida, Deborah A Nichols, Rik Jadrnicek, Ric Miller, James K Walsh, and Kara Griffin. 2012 · 2012
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Learning multilingual named entity recognition from wikipedia
Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, and James R Curran. 2013 · 2013
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Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013)
Isabel Segura Bedmar, Paloma Martínez, and María Herrero Zazo. 2013 · 2013
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Lexicon infused phrase embeddings for named entity resolution
Alexandre Passos, Vineet Kumar, and Andrew McCallum. 2014 · 2014
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A study of active learning methods for named entity recognition in clinical text
Yukun Chen, Thomas A Lasko, Qiaozhu Mei, Joshua C Denny, and Hua Xu. 2015 · 2015
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Joint named entity recognition and disambiguation
Gang Luo, Xiaojing Huang, Chin-Yew Lin, and Zaiqing Nie. 2015 · 2015
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Named entity recognition with bidirectional lstm-cnns
Jason PC Chiu and Eric Nichols. 2016 · 2016
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Anonymizing and sharing medical text records
Xiao-Bai Li and Jialun Qin. 2017 · 2017
A generic framework for privacy preserving deep learning
Theo Ryffel, Andrew Trask, Morten Dahl, Bobby Wagner, Jason Mancuso, Daniel Rueckert, and Jonathan Passerat-Palmbach. 2018 · 2018
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Named entity recognition using BERT-BiLSTM-CRF for chinese electronic health records
Zhenjin Dai, Xutao Wang, Pin Ni, Yuming Li, Gangmin Li, and Xuming Bai. 2019 · 2019
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Deep reinforcement learning-based text anonymization against private-attribute inference
Ahmadreza Mosallanezhad, Ghazaleh Beigi, and Huan Liu. 2019 · 2019
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Semantic finlex: Transforming, publishing, and using finnish legislation and case law as linked open data on the web
Arttu Oksanen, J Tuominen, E Mäkelä, M Tamper, Aki Hietanen, and Eero Hyvönen. 2019 · 2019
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Federated machine learning: Concept and applications
Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong. 2019 · 2019
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Snorkel: Rapid training data creation with weak supervision
Alexander Ratner, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré. 2017 · 2017
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Deep learning is robust to massive label noise
David Rolnick, Andreas Veit, Serge Belongie, and Nir Shavit. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Anonymization of unstructured data via named-entity recognition
Fadi Hassan, Josep Domingo-Ferrer, and Jordi Soria-Comas. 2018 · 2018
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Rethinking generalization of neural models: A named entity recognition case study
Jinlan Fu, Pengfei Liu, and Qi Zhang. 2020 · 2020
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Federated learning: Challenges, methods, and future directions
Tian Li, Anit Kumar Sahu, Ameet Talwalkar, and Virginia Smith. 2020 · 2020
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Extensive error analysis and a learning-based evaluation of medical entity recognition systems to approximate user experience
Isar Nejadgholi, Kathleen C. Fraser, and Berry De Bruijn. 2020 · 2020
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Adversarial attacks on deep-learning models in natural language processing: A survey
Wei Emma Zhang, Quan Z Sheng, Ahoud Alhazmi, and Chenliang Li. 2020 · 2020
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