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Random survival forest to predict transplant-eligible newly diagnosed multiple myeloma outcome including FDG-PET radiomics: a combined analysis of two independent prospective European trials

Bastien Jamet, Ludivine Morvan, Cristina Nanni, Anne-Victoire Michaud, Clément Bailly, Stéphane Chauvie, Philippe Moreau, Cyrille Touzeau, Elena Zamagni, Caroline Bodet‐Milin, Françoise Kraeber‐Bodéré, Diana Mateus, Thomas Carlier

2020European Journal of Nuclear Medicine and Molecular Imaging57 citationsDOI

Topics & Concepts

MedicinePositron emission tomographyMultiple myelomaClinical trialRadiologyProspective cohort studyFluorodeoxyglucoseNuclear medicineInternal medicineOncologyMultiple Myeloma Research and TreatmentsRadiomics and Machine Learning in Medical ImagingAI in cancer detection
Random survival forest to predict transplant-eligible newly diagnosed multiple myeloma outcome including FDG-PET radiomics: a combined analysis of two independent prospective European trials | Litcius