APASL-ACLF Research Consortium-Artificial Intelligence (AARC-AI) model precisely predicts outcomes in acute-on-chronic liver failure patients.

Nipun VermaAshok ChoudhuryVirendra Singh Ajay Kumar DusejaManum Al-MahtabHarshad DevarbhaviChundamannil E EapenAshish Goel Qin Ning Zhongping DuanSaeed HamidWasim JafriAmna Shubhan ButtAkash ShuklaSoek-Siam TanDong Joon KimJinhua HuAjit SoodOmesh GoyalVandana MidhaHashmik GhaznianManoj Kumar SahuGuan Huei LeeSombat TreeprasertsukSamir ShahLaurentius A LesmanaRinaldi C LesmanaV G Mohan PrasadShiv Kumar Sarinnull null

Published in: Liver international : official journal of the International Association for the Study of the Liver (2022)

The performance of the AARC-AI model exceeds the standard models for outcome predictions in ACLF. An AI-based decision tree can reliably undertake severity-based stratification of patients for timely interventions.

Keyphrases

artificial intelligence
liver failure
end stage renal disease
newly diagnosed
chronic kidney disease
deep learning
prognostic factors
big data
hepatitis b virus
patient reported outcomes
adipose tissue
patient reported
acute respiratory distress syndrome
mechanical ventilation