A Deep Learning Framework for Personalized Dynamic Diagnosis of Graft Fibrosis after Liver Transplantation Using Longitudinal Data-Reference-Cited by-同舟云学术

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A Deep Learning Framework for Personalized Dynamic Diagnosis of Graft Fibrosis after Liver Transplantation Using Longitudinal Data

Published:2022 Issue: Volume: Page:
ISSN:1556-5068
Container-title:SSRN Electronic Journal
language:en
Short-container-title:SSRN Journal

Author:

Azhie Amirhossein,Sharma Divya,Sheth Priya,Qazi Arisar Fakhar Ali,Zaya Rita,Naghibzadeh Maryam,Duan Kai,Fischer Sandra,Patel Keyur,Tsien Cynthia,Selzner Nazia,Lilly Leslie,Jaeckel Elmar,Xu Wei,Bhat Mamatha

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference42 articles.

1. Performance of transient elastography and serum fibrosis biomarkers for non-invasive evaluation of recurrent fibrosis after liver transplantation: A meta-analysis;M Bhat;PLOS ONE,2017

2. Serum fibrosis biomarkers predict death and graft loss in liver transplantation recipients;M Bhat;Liver Transplantation,2015

3. Liver Stiffness 1 Year After Transplantation Predicts Clinical Outcomes in Patients With Recurrent Hepatitis C;G Crespo;American Journal of Transplantation,2014

4. Progression of liver fibrosis in post-transplant hepatitis C: Mechanisms, assessment and treatment;M Berenguer;Journal of Hepatology,2013

5. Impact of fibrosis progression on clinical outcome in patients treated for post-transplant hepatitis C recurrence;R Dhanasekaran;Liver Int. Nov,2015

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