crossrefAI2026-05-09
Machine Learning Models for Predicting Post-Hepatectomy Liver Failure: A Systematic Review
Calin Muntean, Vasile Gaborean, Razvan Constantin Vonica, Sebastian Aurelian Stefaniga, Alaviana Monique Faur, Catalin Vladut Ionut Feier
Background and Objectives: Post-hepatectomy liver failure (PHLF) remains the leading cause of mortality following hepatic resection, with reported incidence rates ranging from 1.2% to 32%. Traditional scoring systems such as the Child–Pugh score, Model for End-Stage Liver Disease…