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Medical report generation is a challenging task since it is time-consuming and requires expertise from experienced radiologists.
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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Generating radiology reports via memory-driven transformer
Zhihong Chen, Yan Song, Tsung-Hui Chang, and Xiang Wan · 2010
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Autoencoders, unsupervised learning, and deep architectures
Pierre Baldi · 2012
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Efficient multi-label classification with many labels
Wei Bi and James Kwok · 2013
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Meteor universal: Language specific translation evaluation for any target language
Michael Denkowski and Alon Lavie · 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 · 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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On the automatic generation of medical imaging reports
Baoyu Jing, Pengtao Xie, and Eric Xing · 2017
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Knowing when to look: Adaptive attention via a visual sentinel for image captioning
Jiasen Lu, Caiming Xiong, Devi Parikh, and Richard Socher · 2017
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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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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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Hybrid retrieval-generation reinforced agent for medical image report generation
Christy Y Li, Xiaodan Liang, Zhiting Hu, and Eric P Xing · 2018
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Align, attend and locate: Chest x-ray diagnosis via contrast induced attention network with limited supervision
Jingyu Liu, Gangming Zhao, Yu Fei, Ming Zhang, Yizhou Wang, and Yizhou Yu · 2019
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Jianbo Yuan, Haofu Liao, Rui Luo, and Jiebo Luo · 2019
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Vispi: Automatic visual perception and interpretation of chest x-rays
Xin Li, Rui Cao, and Dongxiao Zhu · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Multimodal recurrent model with attention for automated radiology report generation
Yuan Xue, Tao Xu, L Rodney Long, Zhiyun Xue, Sameer Antani, George R Thoma, and Xiaolei Huang · 2018
Cited alongside, same era.
Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs
Alistair EW Johnson, Tom J Pollard, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Yifan Peng, Zhiyong Lu, Roger G Mark, Seth J Berkowitz, and Steven Horng · 2019
Cited alongside, same era.
Two-stream collaborative network for multi-label chest x-ray image classification with lung segmentation
Bingzhi Chen, Zheng Zhang, Jianyong Lin, Yi Chen, and Guangming Lu
Cited in the paper.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton
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Chest x-ray report generation through fine-grained label learning
Tanveer Syeda-Mahmood, Ken CL Wong, Yaniv Gur, Joy T Wu, Ashutosh Jadhav, Satyananda Kashyap, Alexandros Karargyris, Anup Pillai, Arjun Sharma, Ali Bin Syed, et al · 2020
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Contrastive attention for automatic chest x-ray report generation
Fenglin Liu, Changchang Yin, Xian Wu, Shen Ge, Ping Zhang, and Xu Sun · 2021
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