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Various deep learning algorithms have been developed to analyze different types of clinical data including clinical text classification and extracting information from 'free text' and so on.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Transductive inference for text classification using support vector machines
Thorsten Joachims · 1999
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High-performing feature selection for text classification
Monica Rogati and Yiming Yang · 2002
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A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston · 2008
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Knowledge-based biomedical word sense disambiguation: an evaluation and application to clinical document classification
Vijay N Garla and Cynthia Brandt · 2012
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Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean · 2013
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Distributional semantics resources for biomedical text processing
SPFGH Moen and Tapio Salakoski2 Sophia Ananiadou · 2013
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Recursive deep models for discourse parsing
Jiwei Li, Rumeng Li, and Eduard Hovy · 2014
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Bidirectional lstm-crf models for sequence tagging
Zhiheng Huang, Wei Xu, and Kai Yu · 2015
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Boosting named entity recognition with neural character embeddings
Cicero Nogueira dos Santos and Victor Guimaraes · 2015
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Very deep convolutional networks for text classification
Alexis Conneau, Holger Schwenk, Loïc Barrault, and Yann Lecun · 2016
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Deep learning based parts of speech tagger for bengali
Md Fasihul Kabir, Khandaker Abdullah-Al-Mamun, and Mohammad Nurul Huda · 2016
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Recurrent neural network for text classification with multi-task learning
Pengfei Liu, Xipeng Qiu, and Xuanjing Huang · 2016
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Predicting early psychiatric readmission with natural language processing of narrative discharge summaries
A Rumshisky, M Ghassemi, T Naumann, P Szolovits, VM Castro, TH McCoy, and RH Perlis · 2016
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Using distributed representations to disambiguate biomedical and clinical concepts
Stephan Tulkens, Simon Suster, and Walter Daelemans · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al · 2016
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Drug drug interaction extraction from biomedical literature using syntax convolutional neural network
Zhehuan Zhao, Zhihao Yang, Ling Luo, Hongfei Lin, and Jian Wang · 2016
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Text classification improved by integrating bidirectional lstm with two-dimensional max pooling
Peng Zhou, Zhenyu Qi, Suncong Zheng, Jiaming Xu, Hongyun Bao, and Bo Xu · 2016
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A neural joint model for entity and relation extraction from biomedical text
Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder · 2018
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Incorporating syntactic dependencies into semantic word vector model for medical text processing
Maia Iyer, Christopher Zou, and Xiao Luo · 2018
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Cross-type biomedical named entity recognition with deep multi-task learning
Xuan Wang, Yu Zhang, Xiang Ren, Yuhao Zhang, Marinka Zitnik, Jingbo Shang, Curtis Langlotz, and Jiawei Han · 2018
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Attention-based lstm for psychological stress detection from spoken language using distant supervision
Genta Indra Winata, Onno Pepijn Kampman, and Pascale Fung · 2018
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Leveraging biomedical resources in bi-lstm for drug-drug interaction extraction
Bo Xu, Xiufeng Shi, Zhehuan Zhao, and Wei Zheng · 2018
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Fei Li, Meishan Zhang, Guohong Fu, and Donghong Ji · 2017
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An attention-based bilstm-crf approach to document-level chemical named entity recognition
Ling Luo, Zhihao Yang, Pei Yang, Yin Zhang, Lei Wang, Hongfei Lin, and Jian Wang · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Entity extraction in biomedical corpora: An approach to evaluate word embedding features with pso based feature selection
Shweta Yadav, Asif Ekbal, Sriparna Saha, and Pushpak Bhattacharyya · 2017
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Classification of hepatocellular carcinoma stages from free-text clinical and radiology reports
Wen-wai Yim, Sharon W Kwan, Guy Johnson, and Meliha Yetisgen · 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
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Semantic relatedness and similarity of biomedical terms: examining the effects of recency, size, and section of biomedical publications on the performance of word2vec
Yongjun Zhu, Erjia Yan, and Fei Wang · 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
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Improving clinical named entity recognition with global neural attention
Guohai Xu, Chengyu Wang, and Xiaofeng He · 2018
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Deep learning for sentiment analysis: A survey
Lei Zhang, Shuai Wang, and Bing Liu · 2018
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Publicly available clinical bert embeddings
Emily Alsentzer, John R Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, and Matthew McDermott · 2019
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Understanding emotions in text using deep learning and big data
Ankush Chatterjee, Umang Gupta, Manoj Kumar Chinnakotla, Radhakrishnan Srikanth, Michel Galley, and Puneet Agrawal · 2019
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An attention based deep learning model of clinical events in the intensive care unit
Deepak A Kaji, John R Zech, Jun S Kim, Samuel K Cho, Neha S Dangayach, Anthony B Costa, and Eric K Oermann · 2019
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Ncuee at mediqa 2019: Medical text inference using ensemble bert-bilstm-attention model
Lung-Hao Lee, Yi Lu, Po-Han Chen, Po-Lei Lee, and Kuo-Kai Shyu · 2019
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Analysing representations of memory impairment in a clinical notes classification model
Mark Ormerod, Jesús Martínez-del Rincón, Neil Robertson, Bernadette McGuinness, and Barry Devereux · 2019
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Biowordvec, improving biomedical word embeddings with subword information and mesh
Yijia Zhang, Qingyu Chen, Zhihao Yang, Hongfei Lin, and Zhiyong Lu · 2019
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