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Editorial
. 2023 Sep;58(6):636-637.
doi: 10.1111/apt.17651.

Recent advances in fibrosis assessment for metabolic dysfunction-associated fatty liver disease

Angus W Jeffrey  1 , Leon A Adams  1   2
Affiliations
Editorial

Recent advances in fibrosis assessment for metabolic dysfunction-associated fatty liver disease

Angus W Jeffrey et al. Aliment Pharmacol Ther. 2023 Sep.
No abstract available

Keywords: Artificial intelligence, fibrosis quantification, fatty liver; artificial intelligence; fatty liver; fibrosis quantification.

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References

REFERENCES

    1. Chan WL, Chong SE, Chang F, Lai LL, Chuah KH, Nik Mustapha NR, et al. Long-term clinical outcomes of adults with metabolic dysfunction-associated fatty liver disease: a single-centre prospective cohort study with baseline liver biopsy. Hepatol Int. 2023;1-12. https://doi.org/10.1007/s12072-023-10550-9
    1. Loomba R, Ratziu V, Harrison SA, NASH Clinical Trial Design International Working Group. Expert panel review to compare FDA and EMA guidance on drug development and endpoints in nonalcoholic steatohepatitis. Gastroenterology. 2022;162(3):680-688.
    1. Brunt EM. Nonalcoholic fatty liver disease and the ongoing role of liver biopsy evaluation. Hepatol Commun. 2017;1(5):370-378.
    1. Zhan H, Chen S, Gao F, Wang G, Chen S-D, Xi G, et al. AutoFibroNet: a deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD. Aliment Pharmacol Ther. 2023;58:573-584.
    1. Liu F, Goh GBB, Tiniakos D, Wee A, Leow WQ, Zhao JM, et al. qFIBS: an automated technique for quantitative evaluation of fibrosis, inflammation, ballooning, and steatosis in patients with nonalcoholic steatohepatitis. Hepatology. 2020;71(6):1953-1966.

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