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Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer.

C. Abbet, I. Zlobec, B. Bozorgtabar, and J. Thiran. MICCAI (5), volume 12265 of Lecture Notes in Computer Science, page 480-489. Springer, (2020)

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Inti Schubert

Inti Lehmann

Other publications of authors with the same name

An Effective Deep Learning Architecture Combination for Tissue Microarray Spots Classification of H&E Stained Colorectal Images.H. Nguyen, A. Blank, A. Lugli, and I. Zlobec. ISBI, page 1271-1274. IEEE, (2020)Self-Rule to Adapt: Learning Generalized Features from Sparsely-Labeled Data Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Phenotyping.C. Abbet, L. Studer, A. Fischer, H. Dawson, I. Zlobec, B. Bozorgtabar, and J. Thiran. MIDL, volume 143 of Proceedings of Machine Learning Research, page 5-21. PMLR, (2021)A CAD System for Colorectal Cancer from WSI: A Clinically Validated Interpretable ML-based Prototype.P. Neto, D. Montezuma, S. de Oliveira, D. Oliveira, J. Fraga, A. Monteiro, J. Monteiro, L. Ribeiro, S. Gonçalves, S. Reinhard and 3 other author(s). CoRR, (2023)Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer.C. Abbet, I. Zlobec, B. Bozorgtabar, and J. Thiran. MICCAI (5), volume 12265 of Lecture Notes in Computer Science, page 480-489. Springer, (2020)Tumor Budding T-cell Graphs: Assessing the Need for Resection in pT1 Colorectal Cancer Patients.L. Studer, J. Bokhorst, I. Nagtegaal, I. Zlobec, H. Dawson, and A. Fischer. MIDL, volume 227 of Proceedings of Machine Learning Research, page 235-259. PMLR, (2023)Towards IID representation learning and its application on biomedical data.J. Wu, I. Zlobec, M. Lafarge, Y. He, and V. Koelzer. MIDL, volume 172 of Proceedings of Machine Learning Research, page 1375-1402. PMLR, (2022)Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection.C. Abbet, L. Studer, A. Fischer, H. Dawson, I. Zlobec, B. Bozorgtabar, and J. Thiran. Medical Image Anal., (2022)Self-Rule to Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detection.C. Abbet, L. Studer, A. Fischer, H. Dawson, I. Zlobec, B. Bozorgtabar, and J. Thiran. CoRR, (2021)Classification of Intestinal Gland Cell-Graphs Using Graph Neural Networks.L. Studer, J. Wallau, H. Dawson, I. Zlobec, and A. Fischer. ICPR, page 3636-3643. IEEE, (2020)

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Disambiguation of "Zlobec, Inti"

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Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer.

Please choose a person to relate this publication to

Inti Schubert

Inti Lehmann

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Zlobec, Inti"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer.

Please choose a person to relate this publication to

Inti Schubert

Inti Lehmann

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
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Chicago
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Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer.