AI boosts X-Ray accuracy in massive 16,000-Patient trial
NCT ID NCT07497243
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This trial tests whether an artificial intelligence model can help radiologists interpret chest X-rays more accurately and quickly. Researchers will compare diagnoses made with and without AI assistance in 16,000 patients with suspected chest diseases. The goal is to improve the current diagnostic accuracy of around 70% and reduce report generation time.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- Active substance
- AI-assisted X-ray diagnosis system
- What this could lead to
- If successful, this AI tool could help radiologists detect diseases like pneumonia or lung cancer on chest X-rays more accurately and quickly.
- What could go wrong
- This is an early-stage trial that has not yet started recruiting. The AI may not improve accuracy in real-world settings, and results may not apply to all 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
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About 16,000 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
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May 2026
An estimate. Start dates often move.
- Expected to finish
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Nov 2026
An estimate. End dates often move.
- Lead sponsor
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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
Patients scheduled to undergo X-ray examination
- Ages
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Children (under 18), adults (18 to 64) and older adults (65 and over)
- Sex
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Anyone
- Healthy volunteers
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Accepted
You do not need to have the condition being studied to take part.
Show the full entry requirements Hide 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: * Clinically suspected thoracic diseases (such as pneumonia, tuberculosis, or lung cancer) requiring X-ray diagnosis； * Patients providing written informed consent for research data use； * Complete clinical records (including chief complaints, medical history, and laboratory test results) Exclusion Criteria: * Substandard X-ray image quality (including severe motion artifacts, over-/underexposure, or missing anatomical structures) * Pregnant or lactating women
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As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
4 sites. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
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The First Affiliated Hospital of Zhengzhou University
Zhengzhou, China
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Wuhan Union Hospital
Wuhan, Hubei, 430022, China
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Wuhan Union Jinyin Lake Hospital
Wuhan, Hubei, 430022, China
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Wuhan Union West Hospital
Wuhan, Hubei, 430022, China
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