MRI‐Based Machine Learning for Differentiating Borderline From Malignant Epithelial Ovarian Tumors: A Multicenter Study-Reference-Cited by-全球学者库

MRI‐Based Machine Learning for Differentiating Borderline From Malignant Epithelial Ovarian Tumors: A Multicenter Study

Published:2020-02-11 Issue:3 Volume:52 Page:897-904
ISSN:1053-1807
Container-title:Journal of Magnetic Resonance Imaging
language:en
Short-container-title:J Magn Reson Imaging

Author:

Li Yong'ai¹,Jian Junming²³^ORCID,Pickhardt Perry J.⁴,Ma Fenghua⁵,Xia Wei²^ORCID,Li Haiming⁶,Zhang Rui²^ORCID,Zhao Shuhui⁷,Cai Songqi⁸,Zhao Xingyu²³,Zhang Jiayi²^ORCID,Zhang Guofu⁵^ORCID,Jiang Jingxuan⁹,Zhang Yan¹⁰,Wang Keying¹¹,Lin Guangwu¹²,Feng Feng¹³,Lu Jing¹,Deng Lin¹,Wu Xiaodong²,Qiang Jinwei¹^ORCID,Gao Xin²^ORCID

Affiliation:

1. Department of Radiology, Jinshan HospitalFudan University Shanghai China

2. Suzhou Institute of Biomedical Engineering and TechnologyChinese Academy of Sciences Suzhou China

3. University of Science and Technology of China Hefei China

4. Department of RadiologyUniversity of Wisconsin School of Medicine and Public Health Madison Wisconsin USA

5. Department of RadiologyObstetrics and Gynecology Hospital, Fudan University Shanghai China

6. Department of RadiologyCancer Hospital, Fudan University Shanghai China

7. Department of RadiologyXinhua Hospital, Medical College of Shanghai Jiao Tong University Shanghai China

8. Department of RadiologyZhongshan Hospital, Fudan University Shanghai China

9. Department of RadiologyAffiliated Hospital of Nantong University Nantong China

10. Department of RadiologyGuangdong Women and Children Hospital Guangzhou China

11. Department of RadiologyAffiliated Hospital of Xuzhou Medical University Xuzhou China

12. Department of RadiologyHuadong Hospital, Fudan University Shanghai China

13. Department of RadiologyCancer Hospital, Nantong University Nantong China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.27084

Reference37 articles.

1. Ovarian borderline tumors in the 2014 WHO classification: evolving concepts and diagnostic criteria

2. Borderline ovarian tumors: Key points and workshop summary

3. Clinicopathologic Features and Risk Factors for Recurrence of Mucinous Borderline Ovarian Tumors: A Retrospective Study With Follow-up of More Than 10 Years

4. Risk of borderline ovarian tumors among women with benign ovarian tumors: A cohort study

5. Management of borderline ovarian tumours

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