Machine learning improves the accuracy of graft weight prediction in living donor liver transplantation
Mariano Cesare Giglio, Mario Zanfardino, Monica Franzese, Hazem Zakaria, Salah Alobthani, Ahmed Zidan, Islam Ismail Ayoub, Hany Abdelmeguid Shoreem, Boram Lee, Ho‐Seong Han, Andrea Della Penna, Silvio Nadalin, Roberto Ivan Troisi, Dieter Clemens Broering – 26 September 2022 – Precise graft weight (GW) estimation is essential for planning living donor liver transplantation to select grafts of adequate size for the recipient. This study aimed to investigate whether a machine‐learning model can improve the accuracy of GW estimation.