Identification of four novel acute-on-chronic liver failure clusters with distinct clinical trajectories and mortality using machine learning methods.

ML for the first time could identify clusters with distinct phenotypes, trajectories and outcomes in ACLF. Stratification into clusters can address heterogeneity, guide prognosis, recruitment in trials, resource allocation and liver transplant discussions in ACLF.