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

Hepatology. 2021 Oct;74(4):2233-2240. doi: 10.1002/hep.31869. Epub 2021 Aug 10.

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 types

  • Review

MeSH terms

  • Artificial Intelligence*
  • Diagnostic Techniques, Digestive System
  • Humans
  • Liver Cirrhosis* / etiology
  • Liver Cirrhosis* / pathology
  • Neural Networks, Computer
  • Non-alcoholic Fatty Liver Disease* / complications
  • Non-alcoholic Fatty Liver Disease* / diagnosis
  • Risk Assessment / methods
  • Risk Assessment / trends