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Asgari Taghanaki, S., Abhishek, K., Cohen, J. P., Cohen-Adad, J., & Hamarneh, G. (2020). Deep semantic segmentation of natural and medical images: a review. Artificial Intelligence Review, 54(1), 137-178. Lien externe
Gotlieb, N., Azhie, A., Sharma, D., Spann, A., Suo, N.-J., Tran, J., Orchanian-Cheff, A., Wang, B., Goldenberg, A., Chassé, M., Cardinal, H., Cohen, J. P., Lodi, A., Dieude, M., & Bhat, M. (2022). The promise of machine learning applications in solid organ transplantation. npj Digital Medicine, 5(1), 13 pages. Lien externe
Lemay, A., Gros, C., Vincent, O., Liu, Y., Cohen, J. P., & Cohen-Adad, J. (juillet 2021). Benefits of linear conditioning for segmentation using metadata [Communication écrite]. 4th Conference on Medical Imaging with Deep Learning (CMDL 2021), Lubeck, Germany. Lien externe
Lemay, A., Gros, C., Vincent, O., Liu, Y., Cohen, J. P., & Cohen-Adad, J. (juillet 2021). Benefits of Linear Conditioning with Metadata for Image Segmentation [Présentation]. Dans 4th Conference on Medical Imaging with Deep Learning (MIDL 2021). Publié dans Proceedings of Machine Learning Research, 143. Lien externe
Sylvain, T., Luck, M., Cohen, J. P., Cardinal, H., Lodi, A., & Bengio, Y. (mars 2021). Exploring the Wasserstein metric for survival analysis [Communication écrite]. AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges and Applications (SPACA 2021), Palo Alto, CA, USA (13 pages). Lien externe
