Machine Learning-based classification using 18F-FDG PET-derived quantitative parameters in predicting Endometrial Cancer aggressiveness

被引：0
|
作者：
Bezzi, C. [1 ,2 ]
Mapelli, P. [1 ,2 ]
Mathoux, G. [3 ]
Monaco, L. [3 ]
Ghezzo, S. [1 ,2 ]
Bergamini, A. [1 ,4 ]
Fallanca, F. [2 ]
Gajate, A. M. Samanes [2 ]
Vasta, F. [1 ,4 ]
Candotti, G. [1 ,4 ]
Taccagni, G. L. [5 ]
Mangili, G. [4 ]
Gianolli, L. [2 ]
Picchio, M. [1 ,2 ]
机构：
[1] Univ Vita Salute San Raffaele, Milan, Italy
[2] IRCCS San Raffaele Sci Inst, Dept Nucl Med, Milan, Italy
[3] Univ Milano Bicocca, Milan, Italy
[4] IRCCS San Raffaele Sci Inst, Unit Obstet & Gynaecol, Milan, Italy
[5] IRCCS San Raffaele Sci Inst, Pathol Unit, Milan, Italy
来源：
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING | 2022年 / 49卷 / SUPPL 1期
关键词：
D O I：
暂无
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
OP-748
引用
收藏
页码：S244 / S244
页数：1
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