Machine learning based on clinico-biological features integrated 18F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of lung

被引:0
作者
Caiyue Ren
Jianping Zhang
Ming Qi
Jiangang Zhang
Yingjian Zhang
Shaoli Song
Yun Sun
Jingyi Cheng
机构
[1] Fudan University Cancer Hospital,Department of Nuclear Medicine, Shanghai Proton and Heavy Ion Center
[2] Shanghai Proton and Heavy Ion Center,Department of Nuclear Medicine
[3] Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy,Department of Oncology, Shanghai Medical College
[4] Fudan University,Center for Biomedical Imaging
[5] Fudan University,Department of Research and Development
[6] Shanghai Engineering Research Center for Molecular Imaging Probes,undefined
[7] Shanghai Proton and Heavy Ion Center,undefined
来源
European Journal of Nuclear Medicine and Molecular Imaging | 2021年 / 48卷
关键词
Squamous cell carcinoma; Adenocarcinoma; F-FDG PET/CT; Radiomics; Nomogram; Machine learning;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:1538 / 1549
页数:11
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