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AI may solve tricky liver diagnosis puzzle

NCT ID NCT05532345

Knowledge-focused Sponsor: Beijing Friendship Hospital Source: ClinicalTrials.gov ↗

What the study statuses mean

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jul 06, 2026 · Last updated Jul 07, 2026 · Updated 1 time

Summary

This study tests whether artificial intelligence can help doctors tell the difference between drug-induced liver injury and autoimmune hepatitis, two conditions that look very similar. Researchers are building a machine learning model using data from over 2,500 patients. If it works, the tool could make diagnosis faster and more accurate, helping patients get the right treatment sooner.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this AI tool could help doctors quickly and accurately tell apart two similar liver conditions, leading to better treatment decisions.
What could go wrong
This is a retrospective study using existing medical records, so the AI may not work as well in real-time or in different patient populations. The model's accuracy is not yet proven in practice.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

2,583 people

The number who actually took part.

Started

Jul 2022

Finished

May 2023

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Hospitalized patients with a definite diagnosis of DILI and AIH were recruited from all hospitals between January 2009 to December 2025. This study was approved by the Institutional Ethical Review Board (2022-P2-263-01).

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Drug-induced liver injury 1. RUCAM ≥6 and met one of the following biochemical conditions: a.) ALT≥5 ULN, b.) or ALP ≥2 ULN, iii) or ALT≥3 ULN and TBil≥2 ULN. 2. RUCAM was between 3-5, the medical records were further reviewed by the three authors to determine the eligibility. * Autoimmune hepatitis 1. The revised International Autoimmune Hepatitis Group (IAIHG) diagnostic score≥6 points. 2. Liver biopsy available, which is compatible with typical features of AIH. 3. If liver biopsy was unavailable, patients who achieved biochemical resolution after sustained immunosuppressive therapy. Exclusion Criteria: * Drug-induced liver injury 1. Hepatotropic viral infection: hepatitis A, B, C, D and E. 2. Non-hepatotropic viral infection: cytomegalovirus (CMV) and Epstein-Barr virus (EBV), etc. 3. Hypoxic ischemic hepatitis and congestive liver disease. 4. Alcohol consumption: male \>40g/d, female \>20g/d, and ≥5 years. 5. Biliary obstruction, primary biliary cholangitis; primary sclerosing cholangitis. 6. Autoimmune hepatitis. 7. Parasitic infection. 8. Sepsis. 9. Previous liver transplantation or bone marrow transplantation. 10. Pregnancy or lactation. 11. Genetic and metabolic liver diseases. * Autoimmune hepatitis 1. Hepatotropic viral infection: hepatitis A, B, C, D and E. 2. Non-hepatotropic viral infection: cytomegalovirus (CMV) and Epstein-Barr virus (EBV), etc. 3. Hypoxic ischemic hepatitis and congestive liver disease. 4. Alcohol consumption: male \>40g/d, female \>20g/d, and ≥5 years. 5. Biliary obstruction, primary biliary cholangitis; primary sclerosing cholangitis. 6. Drug-induced liver injury. 7. Parasitic infection. 8. Sepsis. 9. Previous liver transplantation or bone marrow transplantation. 10. Pregnancy or lactation. 11. Genetic and metabolic liver diseases.

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Conditions

The condition(s) this trial relates to.

autoimmune hepatitis drug-induced liver injury

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Autoimmune hepatitis Drug induced liver injury

Contacts and locations

Locations

  • Beijing Friendship Hospital, Capital Medical University

    Beijing, 100050, China

More trials for these conditions

Other studies related to the condition(s) this trial covers.