FRI173 - Machine learning models accurately interpret liver histology and are associated with disease progression in patients with primary sclerosing cholangitis

Nate Travis; Vincent Billaut; Harsha Pokkalla; Kishalve Pethia; Oscar Zevallos; Benjamin Glass; Amaro Taylor; Christopher Bowlus; Atsushi Tanaka; Douglas Thorburn; Xiaomin Lu; Ryan Huss; Chuhan Chung; Mani Subramanian; Robert Myers; Andrew Muir; Kris V Kowdley; Zachary Goodman; Aditya Khosla; Andrew Beck; Murray Resnick; Ilan Wapinski; Michael Trauner; Cynthia Levy

doi:10.1016/S0168-8278(20)31451-3

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FRI173 - Machine learning models accurately interpret liver histology and are associated with disease progression in patients with primary sclerosing cholangitis

Journal article

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FRI173 - Machine learning models accurately interpret liver histology and are associated with disease progression in patients with primary sclerosing cholangitis

Nate Travis, Vincent Billaut, Harsha Pokkalla, Kishalve Pethia, Oscar Zevallos, Benjamin Glass, Amaro Taylor, Christopher Bowlus, Atsushi Tanaka, Douglas Thorburn, …

Journal of hepatology, Vol.73, pp.S485-S486

2020-08

DOI: https://doi.org/10.1016/S0168-8278(20)31451-3

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Title: FRI173 - Machine learning models accurately interpret liver histology and are associated with disease progression in patients with primary sclerosing cholangitis
Creators: Nate Travis
Vincent Billaut
Harsha Pokkalla
Kishalve Pethia
Oscar Zevallos
Benjamin Glass
Amaro Taylor
Christopher Bowlus
Atsushi Tanaka
Douglas Thorburn
Xiaomin Lu
Ryan Huss
Chuhan Chung
Mani Subramanian
Robert Myers
Andrew Muir
Kris V Kowdley
Zachary Goodman
Aditya Khosla
Andrew Beck
Murray Resnick
Ilan Wapinski
Michael Trauner
Cynthia Levy
Publication Details: Journal of hepatology, Vol.73, pp.S485-S486
Publisher: Elsevier B.V
Academic Unit: Miller School of Medicine; UMMG Dept of Medicine - Hepatology
Language: English
Resource Type: Journal article
Record Identifier: 991031714397402976