Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study

Summary: Background: Kidney allograft failure is a common cause of end-stage renal disease. We aimed to develop a dynamic artificial intelligence approach to enhance risk stratification for kidney transplant recipients by generating continuously refined predictions of survival using updates of clin...

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Principais autores:	Marc Raynaud, PhD, Olivier Aubert, MD, Gillian Divard, MD, Peter P Reese, ProfMD, Nassim Kamar, ProfMD, Daniel Yoo, MPH, Chen-Shan Chin, PhD, Élodie Bailly, MD, Matthias Buchler, ProfMD, Marc Ladrière, ProfMD, Moglie Le Quintrec, ProfMD, Michel Delahousse, ProfMD, Ivana Juric, MD, Nikolina Basic-Jukic, ProfMD, Marta Crespo, ProfMD, Helio Tedesco Silva, Jr, ProfMD, Kamilla Linhares, MD, Maria Cristina Ribeiro de Castro, ProfMD, Gervasio Soler Pujol, ProfMD, Jean-Philippe Empana, ProfMD, Camilo Ulloa, ProfMD, Enver Akalin, ProfMD, Georg Böhmig, ProfMD, Edmund Huang, MD, Mark D Stegall, ProfMD, Andrew J Bentall, ProfMD, Robert A Montgomery, ProfMD, Stanley C Jordan, ProfMD, Rainer Oberbauer, ProfMD, Dorry L Segev, ProfMD, John J Friedewald, ProfMD, Xavier Jouven, ProfMD, Christophe Legendre, ProfMD, Carmen Lefaucheur, ProfMD, Alexandre Loupy, ProfMD
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2021-12-01
coleção:	The Lancet: Digital Health
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2589750021002090
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