Application of Artificial Intelligence for Diagnosis and Risk Stratification in NAFLD and NASH: The State of the Art.
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.
Duke Scholars
Altmetric Attention Stats
Dimensions Citation Stats
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Risk Assessment
- Non-alcoholic Fatty Liver Disease
- Neural Networks, Computer
- Liver Cirrhosis
- Humans
- Gastroenterology & Hepatology
- Diagnostic Techniques, Digestive System
- Artificial Intelligence
- 3204 Immunology
- 3202 Clinical sciences
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Risk Assessment
- Non-alcoholic Fatty Liver Disease
- Neural Networks, Computer
- Liver Cirrhosis
- Humans
- Gastroenterology & Hepatology
- Diagnostic Techniques, Digestive System
- Artificial Intelligence
- 3204 Immunology
- 3202 Clinical sciences