Radiologic-Radiomic Machine Learning Models for Differentiation of Benign and Malignant Solid Renal Masses: Comparison With Expert-Level Radiologists-Reference-Cited by-同舟云学术

Radiologic-Radiomic Machine Learning Models for Differentiation of Benign and Malignant Solid Renal Masses: Comparison With Expert-Level Radiologists

Published:2020-01 Issue:1 Volume:214 Page:W44-W54
ISSN:0361-803X
Container-title:American Journal of Roentgenology
language:en
Short-container-title:American Journal of Roentgenology

Author:

Sun Xue-Ying¹,Feng Qiu-Xia¹,Xu Xun¹,Zhang Jing¹,Zhu Fei-Peng¹,Yang Yan-Hao²,Zhang Yu-Dong¹

Affiliation:

1. Department of Radiology, the First Affiliated Hospital with Nanjing Medical University, No. 300, Guangzhou Rd, Nanjing, Jiangsu Province 210009, China.

2. Department of Urology, the First Affiliated Hospital with Nanjing Medical University, Nanjing, China.

Publisher

American Roentgen Ray Society

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://www.ajronline.org/doi/pdf/10.2214/AJR.19.21617

Reference29 articles.

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4. Comparisons of Outcome and Prognostic Features Among Histologic Subtypes of Renal Cell Carcinoma

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