Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning

被引：0
|
作者：
Mostafa Nazari
Isaac Shiri
Ghasem Hajianfar
Niki Oveisi
Hamid Abdollahi
Mohammad Reza Deevband
Mehrdad Oveisi
Habib Zaidi
机构：
[1] Shahid Beheshti University of Medical Sciences,Department of Biomedical Engineering and Medical Physics, School of Medicine
[2] Geneva University Hospital,Division of Nuclear Medicine and Molecular Imaging
[3] Iran University of Medical Science,Rajaie Cardiovascular Medical and Research Center
[4] The University of British Columbia,School of Population and Public Health
[5] Kerman University,Department of Radiologic Sciences and Medical Physics, Faculty of Allied Medicine
[6] University of British Columbia,Department of Computer Science
[7] Geneva University,Geneva University Neurocenter
[8] University Medical Center Groningen,Department of Nuclear Medicine and Molecular Imaging, University of Groningen
[9] University of Southern Denmark,Department of Nuclear Medicine
来源：
La radiologia medica | 2020年 / 125卷
关键词：
Computed tomography (CT); Radiomics; Machine learning; Renal cell carcinoma; Fuhrman grading;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：754 / 762
页数：8
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