Personalized survival benefit estimation from living donor liver transplantation with a novel machine learning method for confounding adjustment.

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Bibliographic Details
Title: Personalized survival benefit estimation from living donor liver transplantation with a novel machine learning method for confounding adjustment.
Authors: Gangadhar A; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada; Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada., Hasjim BJ; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada; Department of Surgery, University of California - Irvine, Orange, California, USA., Zhao X; McGill University Health Center, Montreal, Quebec, Canada., Sun Y; Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada., Chon J; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada., Sidhu A; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada., Jaeckel E; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada; Division of Gastroenterology & Hepatology, Department of Medicine, University of Toronto, Toronto, ON, Canada., Selzner N; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada; Division of Gastroenterology & Hepatology, Department of Medicine, University of Toronto, Toronto, ON, Canada., Cattral MS; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada; Department of Surgery, University of Toronto, Toronto, ON, Canada., Sayed BA; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada., Brudno M; Department of Computer Science, University of Toronto, Toronto, ON, Canada; Vector Institute, Toronto, ON, Canada; Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada., McIntosh C; Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada; Department of Computer Science, University of Toronto, Toronto, ON, Canada; Vector Institute, Toronto, ON, Canada; Joint Department of Medical Imaging, University Health Network, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Peter Munk Cardiac Center and Ted Rogers Centre for Heart Research, University Health Network, Toronto, ON, Canada., Bhat M; Transplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, ON, Canada; Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada; Division of Gastroenterology & Hepatology, Department of Medicine, University of Toronto, Toronto, ON, Canada; Vector Institute, Toronto, ON, Canada. Electronic address: Mamatha.Bhat@uhn.ca.
Source: Journal of hepatology [J Hepatol] 2025 Nov; Vol. 83 (5), pp. 1116-1127. Date of Electronic Publication: 2025 May 28.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 8503886 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1600-0641 (Electronic) Linking ISSN: 01688278 NLM ISO Abbreviation: J Hepatol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1600-0641
DOI:10.1016/j.jhep.2025.04.040