Machine learning does not outperform traditional statistical modelling for kidney allograft failure prediction-Reference-Cited by-同舟云学术

Machine learning does not outperform traditional statistical modelling for kidney allograft failure prediction

Published:2023-05 Issue:5 Volume:103 Page:936-948
ISSN:0085-2538
Container-title:Kidney International
language:en
Short-container-title:Kidney International

Author:

Truchot Agathe,Raynaud Marc,Kamar Nassim^ORCID,Naesens Maarten^ORCID,Legendre Christophe,Delahousse Michel,Thaunat Olivier,Buchler Matthias,Crespo Marta,Linhares Kamilla,Orandi Babak J.^ORCID,Akalin Enver^ORCID,Pujol Gervacio Soler,Silva Helio Tedesco,Gupta Gaurav,Segev Dorry L.,Jouven Xavier,Bentall Andrew J.,Stegall Mark D.,Lefaucheur Carmen,Aubert Olivier,Loupy Alexandre

Publisher

Elsevier BV

Subject

Nephrology

Reference53 articles.

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2. Trajectories of glomerular filtration rate and progression to end stage kidney disease after kidney transplantation;Raynaud;Kidney Int,2021

3. Management of kidney transplant recipients by general nephrologists: core curriculum 2019;Voora;Am J Kidney Dis,2019

4. Common infections in kidney transplant recipients;Karuthu;Clin J Am Soc Nephrol,2012

5. Cancer in kidney transplant recipients;Au;Nat Rev Nephrol,2018

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