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Chuhan Chung

Showing results (51-60 of 62) with videos related to

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Hepatology (Baltimore, Md.)|June 10, 2022
IL-31 levels correlate with pruritus in patients with cholestatic and metabolic liver diseases and is farnesoid X receptor responsive in NASHJun Xu, Ya Wang, Mina Khoshdeli, et al.
Clinical Gastroenterology and Hepatology : the Official Clinical Practice Journal of the American Gastroenterological Association|April 30, 2018
Acetyl-CoA Carboxylase Inhibitor GS-0976 for 12 Weeks Reduces Hepatic De Novo Lipogenesis and Steatosis in Patients With Nonalcoholic SteatohepatitisEric J Lawitz, Angie Coste, Fred Poordad, et al.
Hepatology (Baltimore, Md.)|October 18, 2021
Cirrhosis regression is associated with improved clinical outcomes in patients with nonalcoholic steatohepatitisArun J Sanyal, Quentin M Anstee, Michael Trauner, et al.
Hepatology (Baltimore, Md.)|August 1, 2021
A Machine Learning Approach to Liver Histological Evaluation Predicts Clinically Significant Portal Hypertension in NASH CirrhosisJaime Bosch, Chuhan Chung, Oscar M Carrasco-Zevallos, et al.
Gut|February 7, 2023
Liver stiffness thresholds to predict disease progression and clinical outcomes in bridging fibrosis and cirrhosisRohit Loomba, Daniel Q Huang, Arun J Sanyal, et al.
Hepatology (Baltimore, Md.)|March 3, 2020
Cilofexor, a Nonsteroidal FXR Agonist, in Patients With Noncirrhotic NASH: A Phase 2 Randomized Controlled TrialKeyur Patel, Stephen A Harrison, Magdy Elkhashab, et al.
Medrxiv : the Preprint Server for Health Sciences|May 10, 2023
AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trialsJanani S Iyer, Harsha Pokkalla, Charles Biddle-Snead, et al.
Hepatology (Baltimore, Md.)|February 11, 2021
A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASHAmaro Taylor-Weiner, Harsha Pokkalla, Ling Han, et al.
Nature Medicine|August 7, 2024
AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseasesJanani S Iyer, Dinkar Juyal, Quang Le, et al.
Nature Medicine|November 4, 2024
Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitisHanna Pulaski, Stephen A Harrison, Shraddha S Mehta, et al.
Pageof 7

Showing results (51-60 of 62) with videos related to

Sort By:
Pageof 7
Hepatology (Baltimore, Md.)|June 10, 2022
IL-31 levels correlate with pruritus in patients with cholestatic and metabolic liver diseases and is farnesoid X receptor responsive in NASHJun Xu, Ya Wang, Mina Khoshdeli, et al.
Clinical Gastroenterology and Hepatology : the Official Clinical Practice Journal of the American Gastroenterological Association|April 30, 2018
Acetyl-CoA Carboxylase Inhibitor GS-0976 for 12 Weeks Reduces Hepatic De Novo Lipogenesis and Steatosis in Patients With Nonalcoholic SteatohepatitisEric J Lawitz, Angie Coste, Fred Poordad, et al.
Hepatology (Baltimore, Md.)|October 18, 2021
Cirrhosis regression is associated with improved clinical outcomes in patients with nonalcoholic steatohepatitisArun J Sanyal, Quentin M Anstee, Michael Trauner, et al.
Hepatology (Baltimore, Md.)|August 1, 2021
A Machine Learning Approach to Liver Histological Evaluation Predicts Clinically Significant Portal Hypertension in NASH CirrhosisJaime Bosch, Chuhan Chung, Oscar M Carrasco-Zevallos, et al.
Gut|February 7, 2023
Liver stiffness thresholds to predict disease progression and clinical outcomes in bridging fibrosis and cirrhosisRohit Loomba, Daniel Q Huang, Arun J Sanyal, et al.
Hepatology (Baltimore, Md.)|March 3, 2020
Cilofexor, a Nonsteroidal FXR Agonist, in Patients With Noncirrhotic NASH: A Phase 2 Randomized Controlled TrialKeyur Patel, Stephen A Harrison, Magdy Elkhashab, et al.
Medrxiv : the Preprint Server for Health Sciences|May 10, 2023
AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trialsJanani S Iyer, Harsha Pokkalla, Charles Biddle-Snead, et al.
Hepatology (Baltimore, Md.)|February 11, 2021
A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASHAmaro Taylor-Weiner, Harsha Pokkalla, Ling Han, et al.
Nature Medicine|August 7, 2024
AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseasesJanani S Iyer, Dinkar Juyal, Quang Le, et al.
Nature Medicine|November 4, 2024
Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitisHanna Pulaski, Stephen A Harrison, Shraddha S Mehta, et al.
Pageof 7