MAFLDMAFLD-AINCT07305636
AI Models vs Non-Invasive Fibrosis Scores in MAFLD Diagnosis
An observational study of MAFLD and AI (Artificial Intelligence), run by Tanta University at 1 site in Egypt.
Trial summary
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). Read more about this study
- Who is it for?
- Ages 18 days and older
- Conditions the study is for
- MAFLD, AI (Artificial Intelligence)
- How many people
- 522 participants
- Where
- 1 siteEgypt
- Study dates
- 13 May 2025to 30 Nov 2025
- How long will I take part?
- 1 Day
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 days and older
- All sexes
- Child, Adult, Older adult
Study population: Adult Egyptian patients (≥18 years) diagnosed with metabolic associated fatty liver disease (MAFLD) according to international criteria, recruited from the outpatient clinic and FibroScan unit of the Tropical Medicine Department, Faculty of Medicine, Tanta University.
Who may be able to join
- Adults ≥18 years.
- Diagnosed with MAFLD according to international criteria (hepatic steatosis with metabolic dysfunction).
- Valid FibroScan evaluation with available LSM and CAP values.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Assessing the Utility of AI Models in MAFLD Diagnosis: Comparison With Traditional Non-Invasive Fibrosis Scores.
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.
- Conditions
- MAFLD, AI (Artificial Intelligence)
What is being measured
The primary outcome is the main question the study is designed to answer.
Measure diagnostic accuracy of AI models in predicting hepatic fibrosis stage (F0-F4)
Measured: At enrollment (single cross-sectional assessment).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Dec 2025
- Study start13 May 2025
- Primary completion30 Aug 2025
- Study completion30 Nov 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for MAFLDStudies of the same condition, open and under way.
- More trials run by Tanta UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 522 participants (actual)
- Target duration
- 1 Day
Sponsor and investigators
- Lead sponsor
- Tanta University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Nahla Ahmed Khalaf, Tanta University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07305636
- Sponsor's protocol ID
- TANTAU-MAFLD-AI-2025-01
- Acronym
- MAFLD-AI
- Status last verified
- Dec 2025
- First submitted
- 12 Dec 2025
- Last updated
- 26 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 26 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessing the Utility of AI Models in MAFLD Diagnosis: Comparison With Traditional Non-Invasive Fibrosis Scores.
- ClinicalTrials.gov ID
- NCT07305636
- Acronym / sponsor ID
- MAFLD-AI / TANTAU-MAFLD-AI-2025-01
- Conditions
- MAFLD, AI (Artificial Intelligence)
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 522 participants (actual)
- Lead sponsor
- Tanta UniversityUniversity, hospital or other
- Study start
- 13 May 2025 (actual)
- Primary completion
- 30 Aug 2025 (actual)
- Study completion
- 30 Nov 2025 (actual)
- First posted
- 26 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Target follow-up
- 1 Day
Who may qualify
- Ages
- 18 days and older
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- Adult Egyptian patients (≥18 years) diagnosed with metabolic associated fatty liver disease (MAFLD) according to international criteria, recruited from the outpatient clinic and FibroScan unit of the Tropical Medicine Department, Faculty of Medicine, Tanta University.
Key inclusion criteria (3 listed)
- Adults ≥18 years.
- Diagnosed with MAFLD according to international criteria (hepatic steatosis with metabolic dysfunction).
- Valid FibroScan evaluation with available LSM and CAP values.
Key exclusion criteria (6 listed)
- Excessive alcohol intake (>30 g/day for men, >20 g/day for women).
- Chronic viral hepatitis (HBV or HCV).
- Autoimmune hepatitis.
- Known malignancy.
- Pregnancy.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Measure diagnostic accuracy of AI models in predicting hepatic fibrosis stage (F0-F4)
Time frame: At enrollment (single cross-sectional assessment).
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Dec 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of MAFLD and AI (Artificial Intelligence), run by Tanta University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 26 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Measure diagnostic accuracy of AI models in predicting hepatic fibrosis stage (F0-F4) (time frame: At enrollment (single cross-sectional assessment).). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Dec 2025.