Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [18F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer

被引：0
|
作者：
Masatoyo Nakajo
Megumi Jinguji
Atsushi Tani
Hidehiko Kikuno
Daisuke Hirahara
Shinichi Togami
Hiroaki Kobayashi
Takashi Yoshiura
机构：
[1] Department of Radiology,Department of Management Planning Division
[2] Kagoshima University,undefined
[3] Graduate School of Medical and Dental Sciences,undefined
[4] Harada Academy,undefined
[5] Department of Obstetrics and Gynecology,undefined
[6] Kagoshima University,undefined
[7] Graduate School of Medical and Dental Sciences,undefined
来源：
Molecular Imaging and Biology | 2021年 / 23卷
关键词：
Endometrial neoplasms, [; F]-FDG; PET/CT; Machine learning, Prognosis;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：756 / 765
页数：9
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