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AI reads 2 million CT scans to spot hidden diseases

NCT ID NCT07040358

Diagnosis Sponsor: First Affiliated Hospital of Zhejiang University Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

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 This study
Running, but no longer taking on new participants.
Completed
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study aims to create an artificial intelligence (AI) system that can help doctors interpret abdominal CT scans more accurately. Researchers will use data from up to 2 million patients to train the AI to detect and describe problems in the abdomen. The goal is to make diagnoses faster and more reliable, especially for busy hospitals.

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

About 2,000,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Dec 2023

Expected to finish

Jun 2026

An estimate. End dates often move.

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

This study uses a retrospective multicenter cohort comprising approximately 2 million cases of multiphase contrast-enhanced abdominal CT scans. All included imaging data are paired with corresponding radiology reports. The dataset reflects real-world imaging scenarios of various abdominal diseases.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

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: * multiphase contrast-enhanced abdominal CT covering the full abdominal region and corresponding radiology reports matched to the CT images Exclusion Criteria: * CT images with poor diagnostic quality due to artifacts, including but not limited to: Convolution artifacts caused by improper arm positioning (e.g., arms placed alongside the body instead of above the head),Respiratory motion artifacts due to inadequate breath-holding.

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As listed by the trial registrant

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

Abdominal diseases

Contacts and locations

Locations

  • the First Affliated Hospital, Zhejiang University School of Medicine

    Hangzhou, Zhejiang, 310003, China

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