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Complexity of ballooned hepatocyte feature recognition: Defining a training atlas for artificial intelligence-based imaging in NAFLD

Lookup NU author(s): Dr Dina Tiniakos, Professor Quentin AnsteeORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Publication metadata

Author(s): Brunt EM, Clouston AD, Goodman Z, Guy C, Kleiner DE, Lackner C, Tiniakos DG, Wee A, Yeh M, Leow WQ, Chng E, Ren Y, Bee G, Powell EE, Rinella M, Sanyal AJ, Neuschwander-Tetri B, Younossi Z, Charlton M, Ratziu V, Harriso SA, Tai D, Anstee QM

Publication type: Article

Publication status: Published

Journal: Journal of Hepatology

Year: 2022

Volume: 76

Issue: 5

Pages: 1030-1041

Print publication date: 01/05/2022

Online publication date: 24/01/2022

Acceptance date: 07/01/2022

Date deposited: 31/01/2022

ISSN (print): 0168-8278

ISSN (electronic): 1600-0641

Publisher: Elsevier BV

URL: https://doi.org/10.1016/j.jhep.2022.01.011

DOI: 10.1016/j.jhep.2022.01.011

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Funding

Funder referenceFunder name
Intramural Research Program of the NIH, National Cancer Institute (DEK);
LITMUS (Liver Investigation: Testing Marker Utility in Steatohepatitis) consortium funded by the Innovative Medicines Initiative (IMI2) Program of the European Union under Grant Agreement 777377;
Newcastle NIHR Biomedical Research Centre (QMA);
this Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA (QMA, CL, DGT, VR, SH, DT).
supported by Histoindex Pte Ltd (DT, EC, YR);

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