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Details for article 23 of 49 found articles
| Title: |
Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study |
| Author: |
Raynaud, Marc Aubert, Olivier Divard, Gillian Reese, Peter P Kamar, Nassim Yoo, Daniel Chin, Chen-Shan Bailly, Élodie Buchler, Matthias Ladrière, Marc Le Quintrec, Moglie Delahousse, Michel Juric, Ivana Basic-Jukic, Nikolina Crespo, Marta Silva Jr, Helio Tedesco Linhares, Kamilla Ribeiro de Castro, Maria Cristina Soler Pujol, Gervasio Empana, Jean-Philippe Ulloa, Camilo Akalin, Enver Böhmig, Georg Huang, Edmund Stegall, Mark D Bentall, Andrew J Montgomery, Robert A Jordan, Stanley C Oberbauer, Rainer Segev, Dorry L Friedewald, John J Jouven, Xavier Legendre, Christophe Lefaucheur, Carmen Loupy, Alexandre |
| Appeared in: |
The Lancet. Digital health |
| Paging: | Volume 3 () nr. 12 pages e795-e805 |
| Year: |
2021 |
| Contents: | |
| Publisher: |
The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 23 of 49 found articles
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