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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
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
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
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
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