Sparse and Hierarchical Transformer for Survival Analysis on Whole Slide Images-Reference-Cited by-同舟云学术

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Sparse and Hierarchical Transformer for Survival Analysis on Whole Slide Images

Published:2024-01 Issue:1 Volume:28 Page:7-18
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Yan Rui¹^ORCID,Lv Zhilong²^ORCID,Yang Zhidong²^ORCID,Lin Senlin²^ORCID,Zheng Chunhou³^ORCID,Zhang Fa⁴^ORCID

Affiliation:

1. School of Biomedical Engineering, University of Science and Technology of China, Hefei, China

2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

3. School of Artificial Intelligence, Anhui University, Hefei, China

4. School of Medical Technology, Beijing Institute of Technology, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10380963/10226279.pdf?arnumber=10226279

Reference66 articles.

1. SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer

2. Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

3. Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study

4. Graph Attention Multi-instance Learning for Accurate Colorectal Cancer Staging

5. RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification

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