@article{0c6a0db53e7546a2871bb2d9af49ca1c,
title = "Reply: Machine learning models for NAFLD/NASH and cirrhosis diagnosis and staging: Accuracy and routine variables are the success keys",
keywords = "Humans, Non-alcoholic Fatty Liver Disease/diagnosis, Liver Cirrhosis/diagnosis, Machine Learning, Liver/pathology",
author = "Devon Chang and Emily Truong and Mazen Noureddin",
note = "Funding Information: Mazen Noureddin consults for, advises, and received grants from BMS and Gilead. He consults for and advises Altimmune, BI, 89BIO, EchoSens, GSK, Merck, Novo Nordisk, OWL, Pfizer, Roche Diagnostic and Siemens, Terns, and Takeda. He is on the speakers{\textquoteright} bureau and received grants from Madrigal. He received grants from and owns stock in Viking. He received grants from Allergan, Akero, Galectin, Genfit, Conatus, Corcept, Enanta, Madrigal, Novartis, Novo Nordisk, Shire, Terns, and Zydus. He owns stock in Anaetos, Rivus Pharma, CIMA, and ChronWell. The remaining authors declare no conflict of interest.",
year = "2023",
month = may,
day = "1",
doi = "10.1097/HEP.0000000000000211",
language = "English (US)",
volume = "77",
pages = "E105--E106",
journal = "Hepatology",
issn = "0270-9139",
publisher = "Wiley",
number = "5",
}