Network-level prediction of set-shifting deterioration after lower-grade glioma resection.

Mrah, Sofiane; Descoteaux, Maxime; Wager, Michel; Boré, Arnaud; Rheault, François; Thirion, Bertrand; Mandonnet, Emmanuel

Mrah, Sofiane; Descoteaux, Maxime; Wager, Michel; Boré, Arnaud; Rheault, François; Thirion, Bertrand; Mandonnet, Emmanuel.

Afiliación

Mrah S; 1Department of Neurosurgery, Hôpital Lariboisière, AP-HP, Paris, France.
Descoteaux M; 2Sherbrooke Connectivity Imaging Lab, Department of Computer Science, Faculty of Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.
Wager M; 3Imeka Solutions, Sherbrooke, Quebec, Canada.
Boré A; 4Department of Neurosurgery, CHU Poitiers, DACTIM-LMA, CNRS 7348, Poitiers, France.
Rheault F; 3Imeka Solutions, Sherbrooke, Quebec, Canada.
Thirion B; 3Imeka Solutions, Sherbrooke, Quebec, Canada.
Mandonnet E; 5Inria, CEA, Université Paris-Saclay, Palaiseau, France.

J Neurosurg ; : 1-9, 2022 Mar 04.

Article en En | MEDLINE | ID: mdl-35245898

Palabras clave

glioma surgery; machine learning; oncology; random forest; set-shifting; structural disconnection signature

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Neurosurg Año: 2022 Tipo del documento: Article País de afiliación: Francia

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