Martin Vallières
Appointment
Canada CIFAR AI Chair
Pan-Canadian AI Strategy
About
Appointed Canada CIFAR AI Chair – 2020
Martin Vallières is an Assistant Professor in the Department of Computer Science at Université de Sherbrooke and a Canada CIFAR AI Chair.
Vallières is an expert in the field of radiomics and machine learning in oncology. Over the course of his career, he has developed multiple prediction models for different types of cancers. His main research interest is now focused on the graph-based modeling of heterogeneous medical data for improved precision medicine.
Awards
- Cum Laude award - Education Exhibit, Radiological Society of North America, 2021
- Michael S. Patterson Publication Impact Prize in Medical Physics, Canadian Organization of Medical Physicists, 2021
- Rotblat Medal, citation prize, Physics in Medicine and Biology journal, 2018
- Rising Star, Medical Physics Research Training Network, 2015
Relevant Publications
- Raymond, N., Laribi, H., Caru, M., Mitiche, M., Marcil, V., Krajinovic, M., Curnier, D., Sinnett, D., & Vallières, M. (2024). Development of error passing network for optimizing the prediction of VO₂ peak in childhood acute leukemia survivors. In Proceedings of the Conference on Health, Inference, and Learning (pp. 506-521). PMLR.
- Andrearczyk, V., et al. (2023). Automatic head and neck tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge. Medical Image Analysis, 90, 102972.
- Pati, S., et al. (2022). Federated learning enables big data for rare cancer boundary detection. Nature Communications, 13(1), 7346.
- Morin, O., et al. (2021). An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication. Nature Cancer, 2(7), 709-722.
- Zwanenburg, A., et al. (2020). The image biomarker standardization initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology, 295(2), 328-338.