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Although there have been several recent advances in the application of deep learning algorithms to chest x-ray interpretation, we identify three major challenges for the translation of chest x-ray algorithms to the clinical setting.
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MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
Alistair E. W. 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 · 1901
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Two public chest X-ray datasets for computer-aided screening of pulmonary diseases
Stefan Jaeger, Sema Candemir, Sameer Antani, Yì-Xiáng J Wáng, Pu-Xuan Lu, and George Thoma. 2014 · 2014
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The accuracy of mobile teleradiology in the evaluation of chest X-rays
Adam B Schwartz, Gina S Siddiqui, John L Barbieri, Amana F Akhtar, Woojin K Kim, Ryan A Littman-Quinn, Emily S Conant, Narainder D Gupta, Bryan A Pukenas, Parvati H Ramchandani, and et al. 2014 · 2014
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Learning Deep Features for Discriminative Localization
Bolei Zhou, Aditya Khosla, Àgata Lapedriza, Aude Oliva, and Antonio Torralba. 2015 · 2015
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A novel approach for tuberculosis screening based on deep convolutional neural networks. In Medical Imaging 2016: Computer-Aided Diagnosis , Vol. 9785. International Society for Optics and Photonics, 97852W
Sangheum Hwang, Hyo-Eun Kim, Jihoon Jeong M.d, and Hee-Jin Kim. 2016 · 2016
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Adversarial examples in the physical world
Alexey Kurakin, Ian J. Goodfellow, and Samy Bengio. 2016 · 2016
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Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, and Dhruv Batra. 2016 · 2016
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A Study and Comparison of Human and Deep Learning Recognition Performance under Visual Distortions. In 2017 26th International Conference on Computer Communication and Networks (ICCCN) . 1–7
Samuel Dodge and Lina Karam. 2017 · 2017
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Densely Connected Convolutional Networks. 4700–4708
Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q. Weinberger. 2017 · 2017
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Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks
Paras Lakhani and Baskaran Sundaram. 2017 · 2017
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Global Epidemiology of Tuberculosis and Progress Toward Achieving Global Targets - 2017
Adam MacNeil, Philippe Glaziou, Charalambos Sismanidis, Susan Maloney, and Katherine Floyd. 2019 · 2017
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Media messaging in diagnosis of acute CXR pathology: an interobserver study among residents
Guy S. Handelman, Ailin C. Rogers, Zafir Babiker, Michael J. Lee, and Morgan P. McMonagle. 2018 · 2018
Cited alongside, same era.
How far have we come? Artificial intelligence for chest radiograph interpretation
K. Kallianos, J. Mongan, S. Antani, T. Henry, A. Taylor, J. Abuya, and M. Kohli. 2019 · 2018
Cited alongside, same era.
Development and validation of deep learning–based automatic detection algorithm for malignant pulmonary nodules on chest radiographs
Ju Gang Nam, Sunggyun Park, Eui Jin Hwang, Jong Hyuk Lee, Kwang-Nam Jin, Kun Young Lim, Thienkai Huy Vu, Jae Ho Sohn, Sangheum Hwang, Jin Mo Goo, et al · 2018
Cited alongside, same era.
Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction
Seong Ho Park and Kyunghwa Han. 2018 · 2018
Cited alongside, same era.
Computer-aided detection in chest radiography based on artificial intelligence: a survey
Chunli Qin, Demin Yao, Yonghong Shi, and Zhijian Song. 2018 · 2018
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
Awni Y Hannun, Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H Tison, Codie Bourn, Mintu P Turakhia, and Andrew Y Ng. 2019 · 2019
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Artificial intelligence for point of care radiograph quality assessment. In Medical Imaging 2019: Computer-Aided Diagnosis , Vol. 10950. International Society for Optics and Photonics, 109503K
Satyananda Kashyap, Mehdi Moradi, Alexandros Karargyris, Joy T. Wu, Michael Morris, Babak Saboury, Eliot Siegel, and Tanveer Syeda-Mahmood. 2019 · 2019
Later among the works it cites.
Key challenges for delivering clinical impact with artificial intelligence
Christopher Kelly, Alan Karthikesalingam, Mustafa Suleyman, Greg Corrado, and Dominic King. 2019 · 2019
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Design Characteristics of Studies Reporting the Performance of Artificial Intelligence Algorithms for Diagnostic Analysis of Medical Images: Results from Recently Published Papers
Dong Wook Kim, Hye Young Jang, Kyung Won Kim, Youngbin Shin, and Seong Ho Park. 2019 · 2019
Later among the works it cites.
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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. 2018b · 2018
Cited alongside, same era.
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, and Aleksander Madry. 2018 · 2018
Cited alongside, same era.
Deep learning in chest radiography: Detection of findings and presence of change
Ramandeep Singh, Mannudeep K. Kalra, Chayanin Nitiwarangkul, John A. Patti, Fatemeh Homayounieh, Atul Padole, Pooja Rao, Preetham Putha, Victorine V. Muse, Amita Sharma, and Subba R. Digumarthy. 2018 · 2018
Cited alongside, same era.
Feature selection for automatic tuberculosis screening in frontal chest radiographs
Szilárd Vajda, Alexandros Karargyris, Stefan Jaeger, KC Santosh, Sema Candemir, Zhiyun Xue, Sameer Antani, and George Thoma. 2018 · 2018
Cited alongside, same era.
Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study
John R. Zech, Marcus A. Badgeley, Manway Liu, Anthony B. Costa, Joseph J. Titano, and Eric Karl Oermann. 2018 · 2018
Cited alongside, same era.
Deep learning and alternative learning strategies for retrospective real-world clinical data
David Chen, Sijia Liu, Paul Kingsbury, Sunghwan Sohn, Curtis B. Storlie, Elizabeth B. Habermann, James M. Naessens, David W. Larson, and Hongfang Liu. 2019 · 2019
Cited alongside, same era.
Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy: A Machine Learning Experiment to Estimate Treatment Effects from Randomized Trial Data
Tony Duan, Pranav Rajpurkar, Dillon Laird, Andrew Y Ng, and Sanjay Basu. 2019 · 2019
Cited alongside, same era.
Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model
Allison Park, Chris Chute, Pranav Rajpurkar, Joe Lou, Robyn L Ball, Katie Shpanskaya, Rashad Jabarkheel, Lily H Kim, Emily McKenna, Joe Tseng, et al · 2019
Later among the works it cites.
Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization
F. Pasa, V. Golkov, F. Pfeiffer, D. Cremers, and D. Pfeiffer. 2019 · 2019
Later among the works it cites.
Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems
Zhi Zhen Qin, Melissa S. Sander, Bishwa Rai, Collins N. Titahong, Santat Sudrungrot, Sylvain N. Laah, Lal Mani Adhikari, E. Jane Carter, Lekha Puri, Andrew J. Codlin, and Jacob Creswell. 2019 · 2019
Later among the works it cites.
Augmenting the National Institutes of Health Chest Radiograph Dataset with Expert Annotations of Possible Pneumonia
George Shih, Carol C. Wu, Safwan S. Halabi, Marc D. Kohli, Luciano M. Prevedello, Tessa S. Cook, Arjun Sharma, Judith K. Amorosa, Veronica Arteaga, Maya Galperin-Aizenberg, Ritu R. Gill, Myrna C.B. Godoy, Stephen Hobbs, Jean Jeudy, Archana Laroia, Palmi N. Shah, Dharshan Vummidi, Kavitha Yaddanapudi, and Anouk Stein. 2019 · 2019
Later among the works it cites.
High-performance medicine: the convergence of human and artificial intelligence
Eric J Topol. 2019 · 2019
Later among the works it cites.
Bora Uyumazturk, Amirhossein Kiani, Pranav Rajpurkar, Alex Wang, Robyn L Ball, Rebecca Gao, Yifan Yu, Erik Jones, Curtis P Langlotz, Brock Martin, et al · 2019
Later among the works it cites.
Automated abnormality detection in lower extremity radiographs using deep learning
Maya Varma, Mandy Lu, Rachel Gardner, Jared Dunnmon, Nishith Khandwala, Pranav Rajpurkar, Jin Long, Christopher Beaulieu, Katie Shpanskaya, Li Fei-Fei, et al · 2019
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International evaluation of an AI system for breast cancer screening
Scott Mayer McKinney, Marcin Sieniek, Varun Godbole, Jonathan Godwin, Natasha Antropova, Hutan Ashrafian, Trevor Back, Mary Chesus, Greg C. Corrado, Ara Darzi, and et al. 2020 · 2020
Closest in time.
Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases. In Proceedings of the IEEE conference on computer vision and pattern recognition . 2097–2106
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers. 2017 · 2097
Closest in time.