Pancreas Rejection in the Artificial Intelligence Era: New Tool for Signal Patients at Risk.

Emanuel Vigia Luís M RamalheteRita RibeiroInês BarrosBeatriz ChumbinhoEdite FilipeAna PenaLuís BichoAna NobreSofia CarrelhaMafalda SobralJorge LamelasJoão Santos CoelhoAníbal FerreiraHugo Pinto Marques

Published in: Journal of personalized medicine (2023)

Our results indicated that it is feasible to develop successful classifiers for the prediction of graft rejection. The Naive Bayesian generated nomogram can be used for rejection probability prediction, thus supporting clinical decision making.

Keyphrases

artificial intelligence
machine learning
end stage renal disease
decision making
big data
ejection fraction
deep learning
newly diagnosed
chronic kidney disease
squamous cell carcinoma
peritoneal dialysis
hiv infected
patient reported outcomes