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

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

7 July 2020

Behzad Bozorgtabar

Jean-Philippe Thiran

Papers citing "Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer"

7 / 7 papers shown

Title
SimMIL: A Universal Weakly Supervised Pre-Training Framework for Multi-Instance Learning in Whole Slide Pathology Images Yicheng Song Tiancheng Lin Die Peng Su Yang Yi Xu MedIm 31 0 0 10 May 2025
Artificial Intelligence for Digital and Computational Pathology Andrew H. Song Guillaume Jaume Drew F. K. Williamson Ming Y. Lu Anurag J. Vaidya Tiffany R. Miller Faisal Mahmood AI4CE 30 130 0 13 Dec 2023
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images Wei-Chien Wang E. Ahn Da-wei Feng Jinman Kim MedIm 24 27 0 10 Feb 2023
Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysis Linhao Qu Siyu Liu Xiaoyu Liu Manning Wang Zhijian Song 25 56 0 18 Aug 2022
How Transferable Are Self-supervised Features in Medical Image Classification Tasks? T. Truong Sadegh Mohammadi Matthias Lenga 42 45 0 23 Aug 2021
Self-Rule to Multi-Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detection C. Abbet Linda Studer Andreas Fischer H. Dawson I. Zlobec Behzad Bozorgtabar Jean-Philippe Thiran OOD 37 32 0 20 Aug 2021
EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting Hassan Muhammad Chen-Wei Xie C. Sigel M. Doukas L. Alpert William R. Jarnagin Amber L. Simpson Thomas J. Fuchs 19 6 0 26 Jan 2021