View in EDS

AI-based body composition score predicts survival after liver transplantation.

Saved in:
Bibliographic Details
Title: AI-based body composition score predicts survival after liver transplantation.
Authors: Malamutmann E; Department of General, Visceral and Transplantation Surgery, University Medicine Essen, Hufelandstraße 55, Essen, 45147, Germany., Roehrborn F; Department of General, Visceral and Transplantation Surgery, University Medicine Essen, Hufelandstraße 55, Essen, 45147, Germany., Vershinina K; Department of General, Visceral and Transplantation Surgery, University Medicine Essen, Hufelandstraße 55, Essen, 45147, Germany., Koitka S; Institute of Artificial Intelligence, University Medicine Essen, Essen, Germany.; Institute of Radiology and Neuroradiology, University Medicine Essen, Essen, Germany., Jaradat D; Department of General, Visceral and Transplantation Surgery, University Medicine Essen, Hufelandstraße 55, Essen, 45147, Germany.; Department of Surgery, University Hospital Graz, Graz, Austria., Schmitz SM; Department of General, Visceral and Transplantation Surgery, University Medicine Essen, Hufelandstraße 55, Essen, 45147, Germany., Haubold J; Institute of Artificial Intelligence, University Medicine Essen, Essen, Germany., Neumann UP; Department of General, Visceral and Transplantation Surgery, University Medicine Essen, Hufelandstraße 55, Essen, 45147, Germany., Nensa F; Institute of Artificial Intelligence, University Medicine Essen, Essen, Germany.; Institute of Radiology and Neuroradiology, University Medicine Essen, Essen, Germany., Oezcelik A; Department of General, Visceral and Transplantation Surgery, University Medicine Essen, Hufelandstraße 55, Essen, 45147, Germany. arzu.oezcelik@uk-essen.de.; Institute of Sex and Gender Sensetive Medicine, University Medicine Essen, Essen, Germany. arzu.oezcelik@uk-essen.de.
Source: Langenbeck's archives of surgery [Langenbecks Arch Surg] 2025 Oct 22; Vol. 410 (1), pp. 307. Date of Electronic Publication: 2025 Oct 22.
Publication Type: Journal Article
Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 9808285 Publication Model: Electronic Cited Medium: Internet ISSN: 1435-2451 (Electronic) Linking ISSN: 14352443 NLM ISO Abbreviation: Langenbecks Arch Surg Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1435-2451
DOI:10.1007/s00423-025-03885-4