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The automatic generation of radiology reports given medical radiographs has significant potential to operationally and improve clinical patient care.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Toward best practices in radiology reporting
Charles E Kahn Jr, Curtis P Langlotz, Elizabeth S Burnside, John A Carrino, David S Channin, David M Hovsepian, and Daniel L Rubin · 2009
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An overview of MetaMap: historical perspective and recent advances
Alan R Aronson and François-Michel Lang · 2010
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A survey of text summarization extractive techniques
Vishal Gupta and Gurpreet Singh Lehal · 2010
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Software framework for topic modelling with large corpora
Radim Rehurek and Petr Sojka · 2010
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Improving communication of diagnostic radiology findings through structured reporting
Lawrence H Schwartz, David M Panicek, Alexandra R Berk, Yuelin Li, and Hedvig Hricak · 2011
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Generating sequences with recurrent neural networks
Alex Graves · 2013
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Densenet: Implementing efficient convnet descriptor pyramids
Forrest Iandola, Matt Moskewicz, Sergey Karayev, Ross Girshick, Trevor Darrell, and Kurt Keutzer · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollar, and Larry Zitnick · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
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Preparing a collection of radiology examinations for distribution and retrieval
Dina Demner-Fushman, Marc D Kohli, Marc B Rosenman, Sonya E Shooshan, Laritza Rodriguez, Sameer Antani, George R Thoma, and Clement J McDonald · 2015
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Exploring nearest neighbor approaches for image captioning
Jacob Devlin, Saurabh Gupta, Ross Girshick, Margaret Mitchell, and C Lawrence Zitnick · 2015
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Challenges in clinical natural language processing for automated disorder normalization
Robert Leaman, Ritu Khare, and Zhiyong Lu · 2015
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Lung nodule and cancer detection in ct screening
Geoffrey D Rubin · 2015
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Predicting semantic descriptions from medical images with convolutional neural networks
Thomas Schlegl, Sebastian M Waldstein, Wolf-Dieter Vogl, Ursula Schmidt-Erfurth, and Georg Langs · 2015
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Interleaved text/image deep mining on a very large-scale radiology database
Hoo-Chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, and Ronald M Summers · 2015
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Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio · 2015
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An actor-critic algorithm for sequence prediction
Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron Courville, and Yoshua Bengio · 2016
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Self-critical sequence training for image captioning
Steven J Rennie, Etienne Marcheret, Youssef Mroueh, Jerret Ross, and Vaibhava Goel · 2017
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Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers · 2017
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Challenges in data-to-document generation
Sam Wiseman, Stuart M Shieber, and Alexander M Rush · 2017
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Neural text generation: A practical guide
Ziang Xie · 2017
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Boosting image captioning with attributes
Ting Yao, Yingwei Pan, Yehao Li, Zhaofan Qiu, and Tao Mei · 2017
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Elad ET Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Rif A Saurous, and Gal Elidan · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Re-evaluating automatic metrics for image captioning
Mert Kilickaya, Aykut Erdem, Nazli Ikizler-Cinbis, and Erkut Erdem · 2016
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Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, and Dan Jurafsky · 2016
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Chia-Wei Liu, Ryan Lowe, Iulian V Serban, Michael Noseworthy, Laurent Charlin, and Joelle Pineau · 2016
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Learning to read chest X-rays: Recurrent neural cascade model for automated image annotation
Hoo-Chang Shin, Kirk Roberts, Le Lu, Dina Demner-Fushman, Jianhua Yao, and Ronald M Summers · 2016
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Xiaosong Wang, Le Lu, Hoo-chang Shin, Lauren Kim, Isabella Nogues, Jianhua Yao, and Ronald Summers · 2016
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Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, and Laurent Charlin · 2018
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Maskgan: Better text generation via filling in the_
William Fedus, Ian Goodfellow, and Andrew M Dai · 2018
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Producing radiologist-quality reports for interpretable artificial intelligence
William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P Bradley, and Lyle J Palmer · 2018
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Towards automatic report generation in spine radiology using weakly supervised framework
Zhongyi Han, Benzheng Wei, Stephanie Leung, Jonathan Chung, and Shuo Li · 2018
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Unsupervised multimodal representation learning across medical images and reports
Tzu-Ming Harry Hsu, Wei-Hung Weng, Willie Boag, Matthew McDermott, and Peter Szolovits · 2018
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Hybrid retrieval-generation reinforced agent for medical image report generation
Yuan Li, Xiaodan Liang, Zhiting Hu, and Eric P Xing · 2018
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Bimodal network architectures for automatic generation of image annotation from text
Mehdi Moradi, Ali Madani, Yaniv Gur, Yufan Guo, and Tanveer Syeda-Mahmood · 2018
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NegBio: a high-performance tool for negation and uncertainty detection in radiology reports
Yifan Peng, Xiaosong Wang, Le Lu, Mohammadhadi Bagheri, Ronald Summers, and Zhiyong Lu · 2018
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Jonathan Rubin, Deepan Sanghavi, Claire Zhao, Kathy Lee, Ashequl Qadir, and Minnan Xu-Wilson · 2018
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TieNet: Text-image embedding network for common thorax disease classification and reporting in chest X-rays
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, and Ronald M Summers · 2018
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Learning to summarize radiology findings
Yuhao Zhang, Daisy Yi Ding, Tianpei Qian, Christopher D Manning, and Curtis P Langlotz · 2018
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Padchest: A large chest x-ray image dataset with multi-label annotated reports
Aurelia Bustos, Antonio Pertusa, Jose-Maria Salinas, and Maria de la Iglesia-Vayá · 2019
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Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, et al · 2019
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Mimic-cxr: A large publicly available database of labeled chest radiographs
Alistair EW Johnson, Tom J Pollard, Seth Berkowitz, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Roger G Mark, and Steven Horng · 2019
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