PREDICTION OF PCFDNA LEVELS, PROGRESSION-FREE SURVIVAL, AND OVERALL SURVIVAL THROUGH MACHINE-LEARNING MODELS BASED ON MRI-DERIVED RADIOMIC FEATURES IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA

被引：0

作者：

Nocera, G. ^{[1
,2
,3
,4
]}

Pecco, N. ^{[1
,2
,3
]}

Pieri, V ^{[1
,5
]}

Palazzo, L. ^{[1
,5
]}

D'Oria, F. ^{[1
]}

Della Rosa, P. ^{[2
,3
]}

Bailo, M. ^{[4
]}

Finocchiaro, G. ^{[5
]}

Mortini, P. ^{[1
,4
]}

Falini, A. ^{[1
,2
,3
]}

Filippi, M. ^{[1
,5
]}

Berzero, G. ^{[1
,5
]}

Castellano, A. ^{[1
,2
,3
]}

机构：

[1] Univ Vita Salute San Raffaele, Milan, Italy

[2] IRCCS San Raffaele Hosp, Dept Neuroradiol, Milan, Italy

[3] IRCCS San Raffaele Hosp, CERMAC, Milan, Italy

[4] IRCCS San Raffaele Hosp, Dept Neurosurg & Gamma Knife Radiosurg, Milan, Italy

[5] IRCCS San Raffaele Hosp, Dept Neurol, Milan, Italy

来源：

NEURO-ONCOLOGY | 2024年 / 26卷

关键词：

D O I：

10.1093/neuonc/noae144.200

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

引用

页码：V61 / V61

页数：1

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