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Anne-Sophie Giacobbi
Sorbonne University - Laboratoire de Biologie Computationnelle et Quantitative (LCQB), UMR 7238 CNRS
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SCHOLARLY PAPERS
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Scholarly Papers (1)
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1.
Multimodal Integration of Transcriptomics, Proteomics and Radiomics Improves Prediction of Recurrence in Patients with IDH-Mutant Glioma
Number of pages: 54
Posted: 24 Mar 2023
Tiffanie Chouleur
,
Christèle Etchegaray
,
Laura Villain
,
Antoine Lesur
,
Thomas Ferté
,
Marco Rossi
,
Laetitia Andrique
,
Costanza Simoncini
, Anne-Sophie Giacobbi,
Matteo Gambaretti
,
Egesta Lopci
,
Bethania Fernades
,
Gunnar Dittmar
,
Rolf Bjerkvig
,
Boris P. Hejblum
,
Rodolphe Thiébaut
,
Olivier Saut
,
Lorenzo Bello
and
Andreas Bikfalvi
University of Bordeaux - INSERM U1312 BRIC, University of Bordeaux - Inria Monc, IMB, UMR 5251, University of Bordeaux - SISTM team, UMR 1219, Luxembourg Institute of Health (LIH), University of Bordeaux - SISTM team, UMR 1219, University of Milan - Neurosurgical Oncology Unit, University of Bordeaux - INSERM U1312 BRIC, University of Bordeaux - Inria Monc, IMB, UMR 5251, Sorbonne University - Laboratoire de Biologie Computationnelle et Quantitative (LCQB), UMR 7238 CNRS, University of Milan - Department of Oncology and Hemato‐Oncology (DIPO), IRCCS Humanitas Research Hospital - Nuclear Medicine Unit, IRCCS Humanitas Research Hospital - Pathology Unit, Luxembourg Institute of Health (LIH) - Department of Infection and Immunity, University of Bergen - Department of Biomedicine, University of Bordeaux - ISPED, INSERM U1219, Inria BSO, University of Bordeaux - SISTM team, UMR 1219, University of Bordeaux - Inria Monc, IMB, UMR 5251, University of Milan - Neurosurgical Oncology Unit and University of Bordeaux - INSERM U1312 BRIC
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Abstract:
IDH-mutant glioma, machine learning, prediction, radiomics, recurrence, Signature
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