NIMG-14. MACHINE LEARNING-BASED EVALUATION OF STATIC AND DYNAMIC FET-PET FOR THE DETECTION OF PSEUDOPROGRESSION IN PATIENTS WITH IDH-WILDTYPE GLIOBLASTOMA

BACKGROUND: Pseudoprogression (PSP) detection in glioblastoma has important clinical implications and remains a challenging task. With the significant advances provided by machine learning (ML) in health care, we investigated the potential of ML in improving the performance of PET using O-(2-[(18)F]...

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Dades bibliogràfiques
Publicat a:Neuro Oncol
Autors principals: Kebir, Sied, Schmidt, Teresa, Weber, Matthias, Lazaridis, Lazaros, Galldiks, Norbert, Langen, Karl-Josef, Kleinschnitz, Christoph, Hattingen, Elke, Herrlinger, Ulrich, Lohmann, Philipp, Glas, Martin
Format: Artigo
Idioma:Inglês
Publicat: Oxford University Press 2020
Matèries:
Neuroimaging
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC7651138/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/neuonc/noaa215.627
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