AI spots hidden liver disease in routine scans
NCT ID NCT07613827
First seen Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This study tests whether an AI system can help doctors identify patients with fatty liver disease who need specialist care. About 8,000 adults getting routine CT scans will have their images analyzed by AI to flag those at risk. The goal is to see if AI can improve detection and referral compared to standard care.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
AI-guided screening system
What this could lead to
If successful, this could make early detection of serious fatty liver disease faster and more accurate using CT scans already done for other reasons.
What could go wrong
This is an early-stage study testing a new workflow, not a treatment. The AI may not improve detection in real-world settings and could lead to unnecessary referrals.
Disclaimer
Read more
Show less
This is a summary of
the original study
.
Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
Get updates
Get notified about this study
Sign up to get updates when this study changes or when new studies for LIVER FIBROSIS are added.
By submitting, you agree to our Terms of use
Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Show contact details
Enter your email to view the contact information for this study.
By submitting, you agree to our Terms of use
Locations
-
Shengjing Hospital of China Medical University
Shenyang, Liaoning, 110004, China