AI Models vs Non-Invasive Fibrosis Scores in MAFLD Diagnosis

This study evaluates the accuracy of artificial intelligence (AI) models using FibroScan and clinical data to predict hepatic fibrosis in Egyptian patients with metabolic-associated fatty liver disease (MAFLD). The performance of the AI models will be compared with conventional noninvasive fibrosis scores (FIB-4, APRI, NAFLD fibrosis score, and FAST). The goal is to improve early, noninvasive diagnosis of fibrosis and reduce reliance on liver biopsy.

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Key information

Conditions

MAFLD AI (Artificial Intelligence)

Age range

18 day and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Faculty of Medicine

Tanta, Egypt

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Adults ≥18 years.

Diagnosed with MAFLD according to international criteria (hepatic steatosis with metabolic dysfunction).

Valid FibroScan evaluation with available LSM and CAP values.

Exclusion criteria

Excessive alcohol intake (>30 g/day for men, >20 g/day for women).

Chronic viral hepatitis (HBV or HCV).

Autoimmune hepatitis.

Known malignancy.

Pregnancy.

Refusal to participate.

Treatment and study plan

Primary outcomes

Measure diagnostic accuracy of AI models in predicting hepatic fibrosis stage (F0-F4)

Time frame: At enrollment (single cross-sectional assessment).

Sponsors and collaborators

Lead sponsor

Tanta University

Other

Registry information

Official study title

Assessing the Utility of AI Models in MAFLD Diagnosis: Comparison With Traditional Non-Invasive Fibrosis Scores.

Acronym: MAFLD-AI

Important dates

Study start: 2025
Primary completion: 2025
Study completion: 2025
First posted: Dec 26, 2025
Registry last updated: Dec 26, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Completed