CVMIL: Cluster Variance Multiple Instance Learning for Whole Slide Images Survival Prediction

Author:

Chen Shiqi1ORCID,Cai Du2ORCID,Li Chenghang3ORCID,Wang Ruixuan1ORCID,Gao Feng2ORCID

Affiliation:

1. Sun Yat-sen University, China

2. The Sixth Affiliated Hospital, Sun Yat-sen University, China

3. The Hong Kong University of Science and Technology (Guangzhou), China

Publisher

ACM

Reference22 articles.

1. Deep learning

2. Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks

3. [3] Zhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang, Xiangyang Ji, and Yongbing Zhang. TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification. In 35th Conference on Neural Information Processing Systems, volume 34, pages 2136–2147, 2021.

4. [4] Hongrun Zhang, Yanda Meng, Yitian Zhao, Yihong Qiao, Xiaoyun Yang, Sarah E. Coupland, and Yalin Zheng. DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification, March 2022. arXiv:2203.12081.

5. Pan-cancer analysis of the extent and consequences of intratumor heterogeneity;Andor Noemi;Nature Medicine,2016

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