Comparison of MRI Sequences to Predict ATRX Status Using Radiomics-Based Machine Learning.

Nacul Mora, Nabila Gala; Akkurt, Burak Han; Kasap, Dilek; Blömer, David; Heindel, Walter; Mannil, Manoj; Musigmann, Manfred

Nacul Mora, Nabila Gala; Akkurt, Burak Han; Kasap, Dilek; Blömer, David; Heindel, Walter; Mannil, Manoj; Musigmann, Manfred.

Afiliação

Nacul Mora NG; Clinic for Radiology, University of Münster and University Hospital Münster Muenster, Albert-Schweitzer-Campus 1, 48149 Muenster, Germany.
Akkurt BH; Clinic for Radiology, University of Münster and University Hospital Münster Muenster, Albert-Schweitzer-Campus 1, 48149 Muenster, Germany.
Kasap D; Clinic for Radiology, University of Münster and University Hospital Münster Muenster, Albert-Schweitzer-Campus 1, 48149 Muenster, Germany.
Blömer D; Clinic for Radiology, University of Münster and University Hospital Münster Muenster, Albert-Schweitzer-Campus 1, 48149 Muenster, Germany.
Heindel W; Clinic for Radiology, University of Münster and University Hospital Münster Muenster, Albert-Schweitzer-Campus 1, 48149 Muenster, Germany.
Mannil M; Clinic for Radiology, University of Münster and University Hospital Münster Muenster, Albert-Schweitzer-Campus 1, 48149 Muenster, Germany.
Musigmann M; Clinic for Radiology, University of Münster and University Hospital Münster Muenster, Albert-Schweitzer-Campus 1, 48149 Muenster, Germany.

Diagnostics (Basel) ; 13(13)2023 Jun 29.

Article em En | MEDLINE | ID: mdl-37443610

Palavras-chave

ATRX; MRI; artificial intelligence; glioma; neuroimaging; radiomics

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

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