Sun, Roger

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · Apollo - University of Cambridge Repository

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · arXiv

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,441

A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study

Sun, R., Limkin, E. J., Vakalopoulou, M., Dercle, L., Champiat, S., Han, S. R., Verlingue, L., Brandao, D., Lancia, A., Ammari, S., et al. (2018) · The Lancet Oncology

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

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Radiomics to predict outcomes and abscopal response of patients with cancer treated with immunotherapy combined with radiotherapy using a validated signature of CD8 cells

Sun, R., Sundahl, N., Hecht, M., Putz, F., Lancia, A., Rouyar, A., Milic, M., Carré, A., Battistella, E., Alvarez Andres, E., et al. (2020) · Journal for ImmunoTherapy of Cancer

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

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Low-dose irradiation of the gut improves the efficacy of PD-L1 blockade in metastatic cancer patients

Chen, J., Levy, A., Tian, A.-L., Huang, X., Cai, G., Fidelle, M., Rauber, C., Ly, P., Pizzato, E., Sitterle, L., et al. (2025) · Cancer Cell

Cancer Immunotherapy and BiomarkersImmunotherapy and Immune Responses

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