about
Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma.Radiomics and radiogenomics in lung cancer: A review for the clinician.An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomasShape Features of the Lesion Habitat to Differentiate Brain Tumor Progression from Pseudoprogression on Routine Multiparametric MRI: A Multisite StudyMass Effect Deformation Heterogeneity (MEDH) on Gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility studyCombination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomographyRadiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in GlioblastomaPerinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from GranulomasAuthor Correction: Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas
P50
Q47192935-C31F9797-02E9-4B63-BAF7-40417D1FEB16Q47229042-78A7FBD3-C61F-4C8A-80D0-CF47AF7D827AQ50450693-C892914F-D0FD-4EA5-B4F4-3A02CC69AB93Q57460365-842C1423-D417-4FEB-AE91-1C46A48BA1C9Q58618713-A450512C-774D-4162-9DE3-0590499C0AD8Q61800828-111C529E-6C3E-4575-B734-BA73CAB4BD71Q62496255-C7A7B0BE-E2BB-4857-9302-F064AEC64877Q89807657-19CA414D-0E8B-4C9D-8F36-DB2EF6C14FDBQ90608377-A11F5BDC-EBD3-42F3-B5FC-2228A4E35A04Q90975282-34415CBA-8462-401B-9A34-91CEBDE70C4A
P50
description
researcher
@en
wetenschapper
@nl
name
Niha Beig
@en
Niha Beig
@nl
type
label
Niha Beig
@en
Niha Beig
@nl
prefLabel
Niha Beig
@en
Niha Beig
@nl
P31
P496
0000-0002-1150-5886