Role of Machine Learning (ML)-Based Classification Using Conventional 18 F-FDG PET Parameters in Predicting Postsurgical Features of Endometrial Cancer Aggressiveness.

Carolina BezziAlice BergaminiGregory MathouxSamuele GhezzoLavinia MonacoGiorgio CandottiFederico FallancaAna Maria Samanes GajateEmanuela RabaiottiRaffaella CioffiLuca BoccioloneLuigi GianolliGianLuca TaccagniMassimo CandianiGiorgia MangiliPaola MapelliMaria Picchio

Published in: Cancers (2023)

F-FDG PET parameters and clinical data demonstrated ability to characterize the investigated features of EC aggressiveness, providing a non-invasive way to support preoperative stratification of EC patients.

Keyphrases

pet ct
endometrial cancer
machine learning
positron emission tomography
pet imaging
end stage renal disease
computed tomography
ejection fraction
newly diagnosed
chronic kidney disease
big data
deep learning
peritoneal dialysis
prognostic factors
artificial intelligence
patients undergoing
atomic force microscopy