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

Michele Dal BoMaurizio PolanoTamara IusFederica Di CintioAlessia MondelloIvana ManiniEnrico PegoloDaniela CesselliCarla Di LoretoMiran SkrapGiuseppe Toffoli

Published in: Journal of translational medicine (2023)

The contribution of tumor volumetric data, somatic gene mutations and TBM in predicting OS of GG4 patients was defined by ML modeling.

Keyphrases

machine learning
patients undergoing
end stage renal disease
big data
ejection fraction
newly diagnosed
chronic kidney disease
copy number
prognostic factors
peritoneal dialysis
data analysis