The pathological risk score: A new deep learning‐based signature for predicting survival in cervical cancer-Reference-Cited by-同舟云学术

The pathological risk score: A new deep learning‐based signature for predicting survival in cervical cancer

Published:2022-06-28 Issue:2 Volume:12 Page:1051-1063
ISSN:2045-7634
Container-title:Cancer Medicine
language:en
Short-container-title:Cancer Medicine

Author:

Chen Chi¹²,Cao Yuye³,Li Weili³,Liu Zhenyu²⁴,Liu Ping³,Tian Xin³,Sun Caixia¹²,Wang Wuliang⁵,Gao Han¹²,Kang Shan⁶,Wang Shaoguang⁷,Jiang Jingying¹⁸,Chen Chunlin³^ORCID,Tian Jie¹²^ORCID

Affiliation:

1. Beijing Advanced Innovation Center for Big Data‐Based Precision Medicine, School of Medicine and Engineering Beihang University Beijing China

2. CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences Beijing China

3. Department of Obstetrics and Gynecology Nanfang Hospital, Southern Medical University Guangzhou China

4. School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

5. Department of Obstetrics and Gynecology The Second Affiliated Hospital of He' nan Medical University Zhengzhou China

6. Department of Gynecology Fourth Hospital Hebei Medical University Shijiazhuang China

7. Department of Gynecology Yantai Yuhuangding Hospital Yantai China

8. Key Laboratory of Big Data‐Based Precision Medicine (Beihang University) Ministry of Industry and Information Technology Beijing China

Funder

Guangzhou Municipal Science and Technology Bureau

National Natural Science Foundation of China

National Science and Technology Program during the Twelfth Five-year Plan Period

Natural Science Foundation of Beijing Municipality

Natural Science Foundation of Guangdong Province

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

Wiley

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cam4.4953

Reference37 articles.

1. World Health Organization. International Agency for Research on Cancer.2020.

2. Cancer of the cervix uteri

3. Guidelines for the Treatment of Recurrent and Metastatic Cervical Cancer

4. A microRNA expression signature for cervical cancer prognosis;Hu X;J Cell Biochem,2010

5. Tumor–stroma ratio is an independent predictor for survival in early cervical carcinoma

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