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We present RadGraph2, a novel dataset for extracting information from radiology reports that focuses on capturing changes in disease state and device placement over time.
Hd-cnn: hierarchical deep convolutional neural networks for large scale visual recognition
Zhicheng Yan, Hao Zhang, Robinson Piramuthu, Vignesh Jagadeesh, Dennis DeCoste, Wei Di, and Yizhou Yu · 2015
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Information extraction from multi-institutional radiology reports
Saeed Hassanpour and Curtis P Langlotz · 2016
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Characterization of change and significance for clinical findings in radiology reports through natural language processing
Saeed Hassanpour, Graham Bay, and Curtis P Langlotz · 2017
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Yolo9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
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Cotype: Joint extraction of typed entities and relations with knowledge bases
Xiang Ren, Zeqiu Wu, Wenqi He, Meng Qu, Clare R Voss, Heng Ji, Tarek F Abdelzaher, and Jiawei Han · 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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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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Neural fine-grained entity type classification with hierarchy-aware loss
Peng Xu and Denilson Barbosa · 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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Deep hierarchical multi-label classification of chest x-ray images
Haomin Chen, Shun Miao, Daguang Xu, Gregory D Hager, and Adam P Harrison · 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 de-identified publicly available database of chest radiographs with free-text reports
Alistair EW Johnson, Tom J Pollard, Seth J Berkowitz, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Roger G Mark, and Steven Horng · 2019
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Yifan Peng, Shankai Yan, and Zhiyong Lu · 2019
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Toward complete structured information extraction from radiology reports using machine learning
Jackson M Steinkamp, Charles Chambers, Darco Lalevic, Hanna M Zafar, and Tessa S Cook · 2019
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Entity, relation, and event extraction with contextualized span representations
David Wadden, Ulme Wennberg, Yi Luan, and Hannaneh Hajishirzi · 2019
Cited alongside, same era.
Classification of pulmonary nodular findings based on characterization of change using radiology reports
Jianbo Yuan, Henghui Zhu, and Amir Tahmasebi · 2019
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Rad-spatialnet: a frame-based resource for fine-grained spatial relations in radiology reports
Surabhi Datta, Morgan Ulinski, Jordan Godfrey-Stovall, Shekhar Khanpara, Roy F Riascos-Castaneda, and Kirk Roberts · 2020
Cited alongside, same era.
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang · 2020
Cited alongside, same era.
Chexpert++: Approximating the chexpert labeler for speed, differentiability, and probabilistic output
Matthew BA McDermott, Tzu Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, and Peter Szolovits · 2020
The need for medical artificial intelligence that incorporates prior images
Julián N Acosta, Guido J Falcone, and Pranav Rajpurkar · 2022
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Application of artificial intelligence in lung cancer
Hwa-Yen Chiu, Heng-Sheng Chao, and Yuh-Min Chen · 2022
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Cross-modal clinical graph transformer for ophthalmic report generation
Mingjie Li, Wenjia Cai, Karin Verspoor, Shirui Pan, Xiaodan Liang, and Xiaojun Chang · 2022
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Optimizing the breast imaging report for today and tomorrow, 2022
Anika L McGrath, Geraldine McGinty, Wendie A Berg, Ellen B Mendelson, Michele B Drotman, Richard L Ellis, and Curtis P Langlotz · 2022
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Structured understanding of assessment and plans in clinical documentation
Doron Stupp, Ronnie Barequet, I-Ching Lee, Eyal Oren, Amir Feder, Ayelet Benjamini, Avinatan Hassidim, Yossi Matias, Eran Ofek, and Alvin Rajkomar · 2022
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Cited alongside, same era.
Tree-cnn: a hierarchical deep convolutional neural network for incremental learning
Deboleena Roy, Priyadarshini Panda, and Kaushik Roy · 2020
Cited alongside, same era.
Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y Ng, and Matthew P Lungren · 2020
Cited alongside, same era.
Domain-specific language model pretraining for biomedical natural language processing
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, and Hoifung Poon · 2021
Cited alongside, same era.
Diagnostic surveillance of high-grade gliomas: towards automated change detection using radiology report classification
Tommaso Di Noto, Chirine Atat, Eduardo Gamito Teiga, Monika Hegi, Andreas Hottinger, Meritxell Bach Cuadra, Patric Hagmann, and Jonas Richiardi · 2021
Cited alongside, same era.
Interpreting chest x-rays via cnns that exploit hierarchical disease dependencies and uncertainty labels
Hieu H Pham, Tung T Le, Dat Q Tran, Dat T Ngo, and Ha Q Nguyen · 2021
Cited alongside, same era.
Extracting clinical terms from radiology reports with deep learning
Kento Sugimoto, Toshihiro Takeda, Jong-Hoon Oh, Shoya Wada, Shozo Konishi, Asuka Yamahata, Shiro Manabe, Noriyuki Tomiyama, Takashi Matsunaga, Katsuyuki Nakanishi, et al · 2021
Cited alongside, same era.
Chest imagenome dataset for clinical reasoning
Joy T Wu, Nkechinyere N Agu, Ismini Lourentzou, Arjun Sharma, Joseph A Paguio, Jasper S Yao, Edward C Dee, William Mitchell, Satyananda Kashyap, Andrea Giovannini, et al · 2021
Cited alongside, same era.
Radbert: Adapting transformer-based language models to radiology
An Yan, Julian McAuley, Xing Lu, Jiang Du, Eric Y Chang, Amilcare Gentili, and Chun-Nan Hsu · 2022
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Knowledge matters: Chest radiology report generation with general and specific knowledge
Shuxin Yang, Xian Wu, Shen Ge, S Kevin Zhou, and Li Xiao · 2022
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Evaluating progress in automatic chest x-ray radiology report generation
Feiyang Yu, Mark Endo, Rayan Krishnan, Ian Pan, Andy Tsai, Eduardo Pontes Reis, Eduardo Kaiser Ururahy Nunes Fonseca, Henrique Min Ho Lee, Zahra Shakeri Hossein Abad, Andrew Y. Ng, Curtis P. Langlotz, Vasantha Kumar Venugopal, and Pranav Rajpurkar · 2022
Later among the works it cites.
Multimodal image-text matching improves retrieval-based chest x-ray report generation
Jaehwan Jeong, Katherine Tian, Andrew Li, Sina Hartung, Fardad Behzadi, Juan Calle, David Osayande, Michael Pohlen, Subathra Adithan, and Pranav Rajpurkar · 2023
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Dynamic graph enhanced contrastive learning for chest x-ray report generation
Mingjie Li, Bingqian Lin, Zicong Chen, Haokun Lin, Xiaodan Liang, and Xiaojun Chang · 2023
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Foundation models for generalist medical artificial intelligence
Michael Moor, Oishi Banerjee, Zahra Shakeri Hossein Abad, Harlan M Krumholz, Jure Leskovec, Eric J Topol, and Pranav Rajpurkar · 2023
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The current and future state of ai interpretation of medical images
Pranav Rajpurkar and Matthew P Lungren · 2023
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Medklip: Medical knowledge enhanced language-image pre-training
Chaoyi Wu, Xiaoman Zhang, Ya Zhang, Yanfeng Wang, and Weidi Xie · 2023
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