Structured dataset documentation: a datasheet for CheXpert

J. Irvin, P. Rajpurkar, M. Ko, Y. Yu, S. Ciurea-Ilcus, C. Chute, H. Marklund, B. Haghgoo, R. Ball, K. Shpanskaya, J. Seekins, D. A. Mong, S. S. Halabi, J. K. Sandberg, R. Jones, D. B. Larson, C. P. Langlotz, B. N. Patel, M. P. Lungren, and A. Y. Ng, “CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparisonir,” 2019. [Online]. Available: https://arxiv.org/abs/1901.07031

Original

1901

Earlier work this paper cites.

D. M. Hansell, A. A. Bankier, H. MacMahon, T. C. McLoud, N. L. Müller, and J. Remy, “Fleischner Society: Glossary of Terms for Thoracic Imaging,” Radiology , vol. 246, no. 3, pp. 697–722, mar 2008

2008

Earlier work this paper cites.

S. Hospital, “Stanford Hospital and Clinics / Lucile Packard Children”s Hospital Notice of Privacy Practices, 2013 version,” Sep. 2013. [Online]. Available: https://stanfordhealthcare.org/content/dam/SHC/patientsandvisitors/patient-privacy/docs/100-598-noticeofprivacypractices-english-2013-final.pdf

2013

Earlier work this paper cites.

T. Gebru, J. Morgenstern, B. Vecchione, J. W. Vaughan, H. Wallach, H. Daumé, and K. Crawford, “Datasheets for Datasets v7,” Link to publication 2020-08-06 , 2018. [Online]. Available: https://arxiv.org/abs/1803.09010

Original

2018

Earlier work this paper cites.

J. R. Zech, M. A. Badgeley, M. Liu, A. B. Costa, J. J. Titano, and E. K. Oermann, “Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study,” PLOS Medicine , vol. 15, no. 11, p. e1002683, nov 2018

2018

Earlier work this paper cites.

J. Irvin, P. Rajpurkar, M. Ko, Y. Yu, S. Ciurea-Ilcus, C. Chute, H. Marklund, B. Haghgoo, R. Ball, K. Shpanskaya, J. Seekins, D. A. Mong, S. S. Halabi, J. K. Sandberg, R. Jones, D. B. Larson, C. P. Langlotz, B. N. Patel, M. P. Lungren, and A. Y. Ng, “CheXpert A Large Chest X-Ray Dataset And Competition,” 2019. [Online]. Available: https://stanfordmlgroup.github.io/competitions/chexpert/

2019

Earlier work this paper cites.

——, “CheXPert labeler,” 2019. [Online]. Available: https://github.com/stanfordmlgroup/chexpert-labeler

2019

Cited alongside, same era.

A. E. W. Johnson, T. J. Pollard, N. R. Greenbaum, M. P. Lungren, C. ying Deng, Y. Peng, Z. Lu, R. G. Mark, S. J. Berkowitz, and S. Horng, “MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs,” 2019

2019

Cited alongside, same era.

E. H. P. Pooch, P. L. Ballester, and R. C. Barros, “Can we trust deep learning models diagnosis? The impact of domain shift in chest radiograph classification,” 2019

2019

Cited alongside, same era.

L. Yao, J. Prosky, B. Covington, and K. Lyman, “A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging,” 2019

2019

Cited alongside, same era.

A. Smit, S. Jain, P. Rajpurkar, A. Pareek, A. Y. Ng, and M. P. Lungren, “CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT,” 2020

2020

Later among the works it cites.

N. A. Phillips, P. Rajpurkar, M. Sabini, R. Krishnan, S. Zhou, A. Pareek, N. M. Phu, C. Wang, M. Jain, N. D. Du, S. Q. Truong, A. Y. Ng, and M. P. Lungren, “CheXphoto: 10,000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness,” 2020

2020

Later among the works it cites.

A. J. Larrazabal, N. Nieto, V. Peterson, D. H. Milone, and E. Ferrante, “Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis,” Proceedings of the National Academy of Sciences , vol. 117, no. 23, pp. 12 592–12 594, may 2020

2020

Later among the works it cites.

A. U. Fonseca, G. S. Vieira, F. A. A. M. N. Soares, and R. F. Bulcão-Neto, “A Research Agenda on Pediatric Chest X-Ray: Is Deep Learning Still in Childhood?” 2020

2020