A Causality-Informed Graph Intervention Model for Pancreatic Cancer Early Diagnosis-Reference-Cited by-同舟云学术

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A Causality-Informed Graph Intervention Model for Pancreatic Cancer Early Diagnosis

Published:2024-09 Issue:9 Volume:5 Page:4675-4685
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Li Xinyue¹^ORCID,Guo Rui¹^ORCID,Zhu Hongzhang²^ORCID,Chen Tao³^ORCID,Qian Xiaohua¹^ORCID

Affiliation:

1. Medical Image and Health Informatics Lab, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

2. Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

3. Department of Biliary and Pancreatic Surgery, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China

Funder

Natural Science Foundation of Shanghai

National Natural Science Foundation of China

Young Leading Scientists Cultivation Plan supported by Shanghai Municipal Education Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/10673734/10510889.pdf?arnumber=10510889

Reference51 articles.

1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

2. Early detection of pancreatic cancer

3. Pancreatic cancer

4. Therapeutic developments in pancreatic cancer: current and future perspectives

5. Early Detection of Pancreatic Cancer: Opportunities and Challenges

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