Fil d'Ariane

null Martin Vallières, Ph. D.

Chercheur, IR-CUSM

Programme de recherche sur le cancer

Professeur associé, Département d'oncologie Gerald Bronfman, Faculté de médecine et des sciences de la santé, Université McGill, Université McGill

 

Mots-clés

analyse d'images médicales • apprentissage automatique • réseaux neuronaux graphiques • apprentissage fédéré

Publications choisies

Cliquez sur Pubmed pour voir la liste de mes publications

  • The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.” Radiology vol. 295,2 (2020): 328-338. doi:10.1148/radiol.2020191145. PMID: 32154773.

  • A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities. Vallières M, Freeman CR, Skamene SR, El Naqa I. Phys Med Biol. 2015 Jul 21;60(14):5471-96. doi: 10.1088/0031-9155/60/14/5471. Epub 2015 Jun 29. PMID: 26119045.

  • Leveraging patients' longitudinal data to improve the Hospital One-year Mortality Risk. Laribi H., Raymond N., Taseen R., Poenaru D., Vallières M., Health information science and systems vol. 13,1 23. 4 Mar. 2025, doi:10.1007/s13755-024-00332-4. PMID: 40051409.

  • An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication. Morin, Olivier et al. Nature cancer vol. 2,7 (2021): 709-722. doi:10.1038/s43018-021-00236-2. PMID: 35121948.

  • Development of Error Passing Network for Optimizing the Prediction of VO2 peak in Childhood Acute Leukemia Survivors. Nicolas Raymond N., Laribi H., Caru M., Mitiche M., Marcil V., Krajinovic M., Curnier D., Sinnett D., Vallières M., Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:506-521.