Metabolite selection for machine learning in childhood brain tumour classification

Author:

Zhao Dadi12ORCID,Grist James T.12ORCID,Rose Heather E.L.12ORCID,Davies Nigel P.123ORCID,Wilson Martin4ORCID,MacPherson Lesley5,Abernethy Laurence J.6,Avula Shivaram6ORCID,Pizer Barry7,Gutierrez Daniel R.89,Jaspan Tim810ORCID,Morgan Paul S.8911ORCID,Mitra Dipayan12,Bailey Simon13ORCID,Sawlani Vijay1415ORCID,Arvanitis Theodoros N.1216ORCID,Sun Yu1217ORCID,Peet Andrew C.12ORCID

Affiliation:

1. Institute of Cancer and Genomic Sciences University of Birmingham Birmingham UK

2. Oncology Birmingham Children's Hospital Birmingham UK

3. Imaging and Medical Physics University Hospitals Birmingham Birmingham UK

4. Centre for Human Brain Health University of Birmingham Birmingham UK

5. Radiology Birmingham Children's Hospital Birmingham UK

6. Radiology Alder Hey Children's Hospital Liverpool UK

7. Paediatric Oncology Alder Hey Children's Hospital Liverpool UK

8. Children's Brain Tumour Research Centre University of Nottingham Nottingham UK

9. Medical Physics Nottingham University Hospitals NHS Trust Nottingham UK

10. Neuroradiology Nottingham University Hospitals NHS Trust Nottingham UK

11. Division of Clinical Neuroscience University of Nottingham Nottingham UK

12. Neuroradiology The Newcastle upon Tyne Hospitals Newcastle upon Tyne UK

13. Paediatric Oncology Great North Children's Hospital Newcastle upon Tyne UK

14. Radiology Queen Elizabeth Hospital Birmingham Birmingham UK

15. School of Psychology University of Birmingham Birmingham UK

16. Institute of Digital Healthcare, WMG University of Warwick Coventry UK

17. University of Birmingham and Southeast University Joint Research Centre for Biomedical Engineering Suzhou China

Funder

Action Medical Research

CHILDREN with CANCER UK

North of England Children’s Cancer Research Fund

Brain Tumour Charity

Publisher

Wiley

Subject

Spectroscopy,Radiology, Nuclear Medicine and imaging,Molecular Medicine

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