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The British Journal of Radiology|February 21, 2023
Applying machine learning classifiers to automate quality assessment of paediatric dynamic susceptibility contrast (DSC-) MRI dataStephen J Powell, Stephanie B Withey, Yu Sun, et al.
Scientific Reports|September 24, 2021
Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumorsJames T Grist, Stephanie Withey, Christopher Bennett, et al.
European Journal of Endocrinology|January 12, 2017
The neuroendocrine sequelae of paediatric craniopharyngioma: a 40-year meta-data analysis of 185 cases from three UK centresTimothy Shao Ern Tan, Leena Patel, Jaya Sujatha Gopal-Kothandapani, et al.
Magnetic Resonance in Medicine|August 9, 2017
Application of pattern recognition techniques for classification of pediatric brain tumors by in vivo 3T 1 H-MR spectroscopy-A multi-center studyNiloufar Zarinabad, Laurence J Abernethy, Shivaram Avula, et al.
NMR in Biomedicine|March 17, 2024
Noise suppression of proton magnetic resonance spectroscopy improves paediatric brain tumour classificationTeddy Zhao, James T Grist, Dorothee P Auer, et al.
The Lancet. Oncology|May 27, 2017
Novel molecular subgroups for clinical classification and outcome prediction in childhood medulloblastoma: a cohort studyEdward C Schwalbe, Janet C Lindsey, Sirintra Nakjang, et al.
NMR in Biomedicine|January 28, 2022
Metabolite selection for machine learning in childhood brain tumour classificationDadi Zhao, James T Grist, Heather E L Rose, et al.
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