Performance or Trust? Why Not Both. Deep AUC Maximization with Self-Supervised Learning for COVID-19 Chest X-ray Classifications

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J. Zhang, P. Xi, A. Ebadi, H. Azimi, S. Tremblay, and A. Wong, “Covid-19 detection from chest x-ray images using imprinted weights approach,” ICLR 2021 Workshop: Machine Learning for Preventing and Combating Pandemics , 2021

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Z. Yuan, Y. Yan, M. Sonka, and T. Yang, “Large-scale robust deep auc maximization: A new surrogate loss and empirical studies on medical image classification,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021

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H. Sowrirajan, J. Yang, A. Y. Ng, and P. Rajpurkar, “Moco pretraining improves representation and transferability of chest x-ray models,” in Proceedings of the Fourth Conference on Medical Imaging with Deep Learning , ser. Proceedings of Machine Learning Research, M. Heinrich, Q. Dou, M. de Bruijne, J. Lellmann, A. Schläfer, and F. Ernst, Eds., vol. 143. PMLR, 07–09 Jul 2021, pp. 728–744. [Online]. Available: https://proceedings.mlr.press/v143/sowrirajan21a.html

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