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Niha Beig

University System of Ohio
H指数:21
被引数:2,452

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Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in glioblastoma

性双态放射基因组学模型确定了不同的成像和生物学途径,这些途径是胶质母细胞瘤总体生存的预后

2020-10-1735
OAAI
CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction

CT衍生的影像学评分可预测I,II期可切除非小细胞肺癌术后辅助化疗的额外益处: 一项回顾性多中心研究,用于结果预测

2020-03-0190
OAAI
Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas (vol 16, 15290, 2019)

定量血管迂曲度: 区分肺肉芽肿和腺癌的潜在CT成像生物标志物 (第16卷,15290,2019)

2019-10-290
OAAI
Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas

肺部CT图像的结节周围和结节内影像特征可区分腺癌和肉芽肿

RADIOLOGY
IF15.2
2019-03-01265
OAAI
Mass Effect Deformation Heterogeneity (MEDH) on Gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility study

钆对比剂T1-weighted MRI的质量效应变形异质性 (MEDH) 与右脑半球胶质母细胞瘤患者生存率降低相关: 一项可行性研究

2019-02-0418
OAAI