Machine learning to improve interpretability of clinical, radiological and panel-based genomic data of glioma grade 4 patients undergoing surgical resection

Machine learning to improve interpretability of clinical, radiological and panel-based genomic data of glioma grade 4 patients undergoing surgical resection

Abstract Background Glioma grade 4 (GG4) tumors, including astrocytoma IDH-mutant grade 4 and the astrocytoma IDH wt are the most common and aggressive primary tumors of the central nervous system. Surgery followed by Stupp protocol still remains the first-line treatment in GG4 tumors. Although Stup...

Full description

Bibliographic Details
Main Authors: Michele Dal Bo, Maurizio Polano, Tamara Ius, Federica Di Cintio, Alessia Mondello, Ivana Manini, Enrico Pegolo, Daniela Cesselli, Carla Di Loreto, Miran Skrap, Giuseppe Toffoli
Format: Article
Language:English
Published: BMC 2023-07-01
Series:Journal of Translational Medicine
Subjects:
Glioma
Machine learning
Prognosis
Carmustine wafer
Tumor mutational burden
Online Access:https://doi.org/10.1186/s12967-023-04308-y

Internet

https://doi.org/10.1186/s12967-023-04308-y

Similar Items