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Machine learning models for medical image analysis often suffer from poor performance on important subsets of a population that are not identified during training or testing.
Why should I trust you?: Explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
Earlier work this paper cites.
Detecting hip fractures with radiologist-level performance using deep neural networks
William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew Bradley, and Lyle Palmer · 2017
Earlier work this paper cites.
MURA: Large dataset for abnormality detection in musculoskeletal radiographs
Pranav Rajpurkar, Jeremy Irvin, Aarti Bagul, Daisy Ding, Tony Duan, Hershel Mehta, Brandon Yang, Kaylie Zhu, Dillon Laird, Robyn L Ball, et al · 2017
Earlier work this paper cites.
Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning
Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Ding, Aarti Bagul, Curtis Langlotz, Katie Shpanskaya, Matthew Lungren, and Andrew Ng · 2017
Earlier work this paper cites.
Disparate impact in big data policing
Andrew D Selbst · 2017
Cited alongside, same era.
Chest x-ray 8: 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
Cited alongside, same era.
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
Pranav Rajpurkar, Jeremy Irvin, Robyn L Ball, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Ding, Aarti Bagul, Curtis P Langlotz, Bhavik N Patel, Kristen W Yeom, Katie Shpanskaya, Francis G Blankenberg, Jayne Seekins, Timothy J Amrhein, David A Mong, Safwan S Halabi, Evan J Zucker, Andrew Y Ng, and Matthew P Lungren · 2018
Cited alongside, same era.
A guide to deep learning in healthcare
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar, Volodymyr Kuleshov, Mark DePristo, Katherine Chou, Claire Cui, Greg Corrado, Sebastian Thrun, and Jeff Dean · 2019
Closest in time.
Exploring large scale public medical image datasets
Luke Oakden-Rayner · 2019
Closest in time.
reproduce-chexnet, 2019
John Zech · 2019
Closest in time.
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