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Accurate Prediction of Clinical Disease Progression in Patients With
Advanced Fibrosis Due to NASH Using a Bayesian Machine Learning Approach
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Reported by Jules Levin
EASL 2018 April 11-15 Paris France
Jeanne C. Latourelle,1 Jing Tu,1 Rahul K. Das,1 Leon Furchtgott,1 Birgit Schoeberl,1 Brielan Smiechowski,1 Bruce W. Church,1 Iya G. Khalil,1 Boris Hayete,1 C. Stephen Djedjos,2 Tuan Nguyen,2
Yuanyuan Xiao,2 Raul Aguilar,2 Guang Chen,2 G. Mani Subramanian,2 Robert P. Myers,2 Vlad Ratziu,3 Nezam Afdhal,4 Jaime Bosch,5 Zachary Goodman,6 Stephen A. Harrison,7 Arun J. Sanyal8
1GNS Healthcare, Cambridge, Massachusetts, USA; 2Gilead Sciences, Inc., Foster City, California, USA; 3Hôpital Universitaire Pitié-Salpêtrière, Paris, France; 4Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA;
5Inselspital, Universitätsspital Bern, Switzerland, and August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Universitat de Barcelona, Spain; 6Inova Fairfax Hospital, Falls Church, Virginia, USA; 7Pinnacle Clinical Research, San Antonio, Texas, USA; 8Virginia Commonwealth University, Richmond, Virginia, USA
References
1. Chalasani N, et al. Hepatology 2018;67:328-357; 2. Tapper EB, Lok AS. N Engl J Med 2017;377:756-68; 3. Friedman N, Koller D. Mach Learn 2003;50:95-125.
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