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

页码：1538 / 1549

页数：11

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