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Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma.
Patel, M; Zhan, J; Natarajan, K; Flintham, R; Davies, N; Sanghera, P; Grist, J; Duddalwar, V; Peet, A; Sawlani, V.
Affiliation
  • Patel M; University of Birmingham, Birmingham, UK; Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
  • Zhan J; Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; The Affiliated Hospital of Qingdao University, Qingdao Shi, Shandong Sheng, China.
  • Natarajan K; Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
  • Flintham R; Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
  • Davies N; Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
  • Sanghera P; University of Birmingham, Birmingham, UK; Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
  • Grist J; University of Birmingham, Birmingham, UK.
  • Duddalwar V; Departments of Radiology, Urology and Biomedical Engineering, University of Southern California, USA.
  • Peet A; University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
  • Sawlani V; University of Birmingham, Birmingham, UK; Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK. Electronic address: Vijay.Sawlani@uhb.nhs.uk.
Clin Radiol ; 76(8): 628.e17-628.e27, 2021 08.
Article in En | MEDLINE | ID: mdl-33941364
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Magnetic Resonance Imaging / Image Interpretation, Computer-Assisted / Glioblastoma / Chemoradiotherapy / Machine Learning Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Clin Radiol Year: 2021 Document type: Article
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Magnetic Resonance Imaging / Image Interpretation, Computer-Assisted / Glioblastoma / Chemoradiotherapy / Machine Learning Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Clin Radiol Year: 2021 Document type: Article