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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Bang, C., Gautier, H., Le, W., Lalonde, A., Bernard, G., Markel, D., Nguyen-Tan, F., Filion, É., O’Sullivan, B., Ayad, T., Christopoulos, A., Bissada, É., Guertin, L., Soulières, D., Létourneau-Guillon, L., Kadoury, S., & Bahig, H. (2025). Dynamic prediction of Radiotherapy toxicities in Head and neck cancer using clinical and imaging data. Radiotherapy and Oncology, 111312-111312. External link
Grajales Lopera, D. O., Le, W., Blanquez-Yeste, V., Dallaire, F., Azzi, F., Delouya, G., Trudel, D., Leblond, F., Ménard, C., & Kadoury, S. (2025). Deployment of a real-time prostate cancer confirmation system with Raman spectroscopy: fine-tuning versus test-time adaptation of 1D CNNs. Biophotonics discovery., 2(03). External link
Grajales, D., Le, W., Dallaire, F., Sheehy, G., David, S., Tran, T., Leblond, F., Ménard, C., & Kadoury, S. (2023, October). Towards Real-Time Confirmation of Breast Cancer in the OR Using CNN-Based Raman Spectroscopy Classification [Paper]. 2nd International Workshop on Cancer Prevention Through Early Detection (CaPTion 2023), Vancouver, BC, Canada. External link
Henique, G., Seok Bang, C., Le, W., Nguyen, F., Filion, É., Soulières, D., O'Sullivan, B., Christopoulos, A., Bissada, É., Ayad, T., Guertin, L., Lalonde, A., Markel, D., Kadoury, S., & Bahig, H. (2025). Head and Neck Cancer Radiotherapy Toxicity Prediction across Intra-Fractional Cone-Beam CTs Using Vision Transformers Networks. International Journal of Radiation Oncology*Biology*Physics, 123(1), e343-e343. Presented at 67th Annual Meeting of the American Society for Radiation Oncology (ASTRO 2025), San Francisco, CA, USA. External link
Henique, G., Bang, C., Markel, D., Le, W., Filion, E., Ngyuen-Tan, P. F., Bahig, H., & Kadoury, S. (2024, May). Dose aware toxicity prediction in head and neck cancer patients using a deformable 3D CNN on Daily CBCT Acquisitions [Paper]. IEEE International Symposium on Biomedical Imaging (ISBI 2024), Athens, Greece (5 pages). External link
Labrecque Langlais, É., Corbin, D., Tastet, O., Hayek, A., Doolub, G., Mrad, S., Tardif, J.-C., Tanguay, J.-F., Marquis-Gravel, G., Tison, G. H., Kadoury, S., Le, W., Gallo, R., Lesage, F., & Avram, R. (2024). Evaluation of stenoses using AI video models applied to coronary angiography. NPJ Digital Medicine, 7, 138 (13 pages). Available
Ouraou, E., Tonneau, M., Le, W., Filion, É., Campeau, M.-P., Vu, T., Doucet, R., Bahig, H., & Kadoury, S. (2025). Predicting early stage lung cancer recurrence and survival from combined tumor motion amplitude and radiomics on free‐breathing 4D‐CT. Medical Physics, 52(3), 1926-1940. Available
Shakeri, S., Le, W., Ménard, C., & Kadoury, S. (2021, April). Deformable Mri To Transrectal Ultrasound Registration For Prostate Interventions With Shape-Based Deep Variational Auto-Encoders [Paper]. 18th IEEE International Symposium on Biomedical Imaging (ISBI 2021), Nice, France. External link
Shams, R., Le, W., Weihs, A., & Kadoury, S. (2021, April). Intensity-Based Wasserstein Distance as a Loss Measure for Unsupervised Deformable Deep Registration [Paper]. 18th IEEE International Symposium on Biomedical Imaging (ISBI 2021), Nice, France. External link
