Publications

Note: The publications presented here are those specific to the work of the MEDomics UdeS laboratory. The list of publications, presentations and activities of Martin Vallières can be found in his Google Scholar and CV.

Journal Papers

• Coming soon.

Conference Papers

• M. Larose, N. Touma, N. Raymond, D. LeBlanc, F. Rasekh, B. Neveu, H. Hovington, M. Vallières, F. Pouliot, L. Archambault (2022). Graph Attention Network for Prostate Cancer Lymph Node Invasion Prediction. In Medical Imaging with Deep Learning 2022.

Preprints

• H. Laribi (2024). Leveraging patients’ longitudinal data to improve the Hospital One-year Mortality Risk. In medRxiv.
• M. Ait Lhaj Loutfi (2024). Unraveling Radiomics Complexity: Strategies for Optimal Simplicity in Predictive Modeling. In arXiv.
• M. Larose (2024). Multi-task Bayesian Model Combining FDG-PET/CT Imaging and Clinical Data for Interpretable High-Grade Prostate Cancer Prognosis. In medRxiv.
• N. Raymond, M. Caru, H. Laribi, M. Mitiche, V. Marcil, M. Krajinovic, D. Curnier, D. Sinnett, M. Vallières (2022). Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors. In arXiv.

Presentations

• M. Ait Lhaj Loutfi (2022). A compliant package with international standards for radiomics analysis of medical images. Scientific day of the Centre interdisciplinaire de recherche en informatique de la santé de l’Université de Sherbrooke (CIRIUS) 2022.
• H. Laribi (2022). Graph neural networks for predicting patient mortality within one year of hospital admission. Scientific day of the Centre interdisciplinaire de recherche en informatique de la santé de l’Université de Sherbrooke (CIRIUS) 2022.
• O. Lefebvre (2022). Precision analysis of predictive uncertainty of machine learning models in medical context. Scientific day of the Centre interdisciplinaire de recherche en informatique de la santé de l’Université de Sherbrooke (CIRIUS) 2022.
• M. Ait Lhaj Loutfi (2022). An international standard compliant tool for radiomic feature extraction from medical images. Scientific day of the Quebec Bioimaging Network 2022.
• N. Raymond (2021). Integration of genomic data in the design of learning models in precision oncology. 88th Acfas Congress.
• A. Ayotte (2021). 3D convolution neural network as a decision support system for multiple renal tumor classification tasks. 88th Acfas Congress.