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Medical image analysis practitioners have embraced big data methodologies.
Rodríguez, A.F., Muller, H.: Ground truth generation in medical imaging: a crowdsourcing-based iterative approach. In: Proceedings of the ACM Workshop on Crowdsourcing for Multimedia (2012)
2012
Earlier work this paper cites.
Le, Q., Mikolov, T.: Distributed representations of sentences and documents. In: Xing, E.P., Jebara, T. (eds.) Proceedings of the 31st International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 32, pp. 1188–1196. PMLR, Bejing, China (22–24 Jun 2014)
2014
Earlier work this paper cites.
Maier-Hein, L., et al
2014
Earlier work this paper cites.
Pennington, J., Socher, R., Manning, C.D.: Glove: Global vectors for word representation. In: Empirical Methods in Natural Language Processing (EMNLP). pp. 1532–1543 (2014), http://www.aclweb.org/anthology/D14-1162
2014
Earlier work this paper cites.
Demner-Fushman, D., et al
2015
Cited alongside, same era.
Rupprecht, C., Peter, L., Navab, N.: Image segmentation in twenty questions. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3314–3322 (June 2015)
2015
Cited alongside, same era.
2015
Cited alongside, same era.
2016
Cited alongside, same era.
Moradi, M., et al
2016
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2018
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