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It is often infeasible or impossible to obtain ground truth labels for medical data.
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 · 1901
Earlier work this paper cites.
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, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, and Andrew Y. Ng · 1901
Earlier work this paper cites.
MIMIC-CXR: A large publicly available database of labeled chest radiographs
Alistair E. W. Johnson, Tom J. Pollard, Seth J. Berkowitz, Nathaniel R. Greenbaum, Matthew P. Lungren, Chih-ying Deng, Roger G. Mark, and Steven Horng · 1901
Earlier work this paper cites.
Publicly Available Clinical BERT Embeddings
Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, and Matthew B. A. McDermott · 1904
Earlier work this paper cites.
Clinically Accurate Chest X-Ray Report Generation
Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, and Marzyeh Ghassemi · 1904
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Supervised machine learning and active learning in classification of radiology reports
Dung H M Nguyen and Jon D Patrick · 2013
Earlier work this paper cites.
Electronic medical record phenotyping using the anchor and learn framework
Yoni Halpern, Steven Horng, Youngduck Choi, and David Sontag · 2016
Earlier work this paper cites.
Cost-Effective Active Learning for Deep Image Classification
Keze Wang, Dongyu Zhang, Ya Li, Ruimao Zhang, and Liang Lin · 2016
Cited alongside, same era.
Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges
Y. Cheng, D. Wang, P. Zhou, and T. Zhang · 2017
Cited alongside, same era.
Exploring the ChestXray14 dataset: problems, December 2017
Luke Oakden-Rayner · 2017
Cited alongside, same era.
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 · 2017
Cited alongside, same era.
Snorkel: Rapid training data creation with weak supervision
Alexander Ratner, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré · 2017
Cited alongside, same era.
Producing radiologist-quality reports for interpretable artificial intelligence
William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, and Lyle J. Palmer · 2018
Later among the works it cites.
Speeding-up convolutional neural networks: A survey
V. Lebedev and V. Lempitsky · 2018
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Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision
Hai Wang and Hoifung Poon · 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
Later among the works it cites.
Chexclusion: Fairness gaps in deep chest x-ray classifiers
Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew McDermott, and Marzyeh Ghassemi · 2020
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Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M. Summers · 2017
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
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Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y Ng, and Matthew P Lungren · 2020
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