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Showing results (101-110 of 117) with videos related to

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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.
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.
Pediatric Radiology|August 1, 2018
Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumoursKaren A Manias, Lisa M Harris, Nigel P Davies, 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.
Acta Neuropathologica Communications|January 11, 2023
Identifying new biomarkers of aggressive Group 3 and SHH medulloblastoma using 3D hydrogel models, single cell RNA sequencing and 3D OrbiSIMS imagingFranziska Linke, James E C Johnson, Stefanie Kern, et al.
Journal of Biomedical Informatics|March 8, 2011
Incremental Gaussian Discriminant Analysis based on Graybill and Deal weighted combination of estimators for brain tumour diagnosisSalvador Tortajada, Elies Fuster-Garcia, Javier Vicente, et al.
Clinical Oncology (Royal College of Radiologists (Great Britain))|January 1, 2023
A National Referral Service for Paediatric Brachytherapy: An Evolving Practice and Outcomes Over 13 YearsM N Gaze, N Smeulders, R Ackwerh, et al.
NMR in Biomedicine|March 25, 2015
Multi-centre reproducibility of diffusion MRI parameters for clinical sequences in the brainMatthew Grech-Sollars, Patrick W Hales, Keiko Miyazaki, et al.
The Lancet. Oncology|October 30, 2025
Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 2: challenges, opportunities, and recommendations for clinical translationAnahita Fathi Kazerooni, Ariana M Familiar, Mariam Aboian, et al.
The Lancet. Oncology|October 30, 2025
Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 1: review of the current state of the artBenjamin H Kann, Arastoo Vossough, Sarah C Brüningk, et al.
Pageof 12

Showing results (101-110 of 117) with videos related to

Sort By:
Pageof 12
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.
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.
Pediatric Radiology|August 1, 2018
Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumoursKaren A Manias, Lisa M Harris, Nigel P Davies, 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.
Acta Neuropathologica Communications|January 11, 2023
Identifying new biomarkers of aggressive Group 3 and SHH medulloblastoma using 3D hydrogel models, single cell RNA sequencing and 3D OrbiSIMS imagingFranziska Linke, James E C Johnson, Stefanie Kern, et al.
Journal of Biomedical Informatics|March 8, 2011
Incremental Gaussian Discriminant Analysis based on Graybill and Deal weighted combination of estimators for brain tumour diagnosisSalvador Tortajada, Elies Fuster-Garcia, Javier Vicente, et al.
Clinical Oncology (Royal College of Radiologists (Great Britain))|January 1, 2023
A National Referral Service for Paediatric Brachytherapy: An Evolving Practice and Outcomes Over 13 YearsM N Gaze, N Smeulders, R Ackwerh, et al.
NMR in Biomedicine|March 25, 2015
Multi-centre reproducibility of diffusion MRI parameters for clinical sequences in the brainMatthew Grech-Sollars, Patrick W Hales, Keiko Miyazaki, et al.
The Lancet. Oncology|October 30, 2025
Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 2: challenges, opportunities, and recommendations for clinical translationAnahita Fathi Kazerooni, Ariana M Familiar, Mariam Aboian, et al.
The Lancet. Oncology|October 30, 2025
Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 1: review of the current state of the artBenjamin H Kann, Arastoo Vossough, Sarah C Brüningk, et al.
Pageof 12