Application of Artificial Intelligence for Diagnosis and Risk Stratification in NAFLD and NASH: The State of the Art. Review uri icon

Overview

abstract

  • The diagnosis of nonalcoholic fatty liver disease and associated fibrosis is challenging given the lack of signs, symptoms and nonexistent diagnostic test. Furthermore, follow up and treatment decisions become complicated with a lack of a simple reproducible method to follow these patients longitudinally. Liver biopsy is the current standard to detect, risk stratify and monitor individuals with nonalcoholic fatty liver disease. However, this method is an unrealistic option in a population that affects about one in three to four individuals worldwide. There is an urgency to develop innovative methods to facilitate management at key points in an individual's journey with nonalcoholic fatty liver disease fibrosis. Artificial intelligence is an exciting field that has the potential to achieve this. In this review, we highlight applications of artificial intelligence by leveraging our current knowledge of nonalcoholic fatty liver disease to diagnose and risk stratify NASH phenotypes.

publication date

  • August 10, 2021

Research

keywords

  • Artificial Intelligence
  • Liver Cirrhosis
  • Non-alcoholic Fatty Liver Disease

Identity

Scopus Document Identifier

  • 85112050640

Digital Object Identifier (DOI)

  • 10.1002/hep.31869

PubMed ID

  • 33928671

Additional Document Info

volume

  • 74

issue

  • 4