X-ray Assisted Diagnostic System

Starting soon

Conditions studied: Chest X-ray for Clinical Evaluation

In brief

X-ray examination is one of the most commonly used imaging modalities, especially chest X-ray, which is routinely performed for hospitalized patients. However, due to the low density resolution of X-ray images, radiologists' ability to diagnose diseases-particularly small lesions-is often affected. Studies have shown that the diagnostic accuracy of radiologists using chest X-rays is only around 70%, which does not meet clinical demands. Based on this, we developed an artificial intelligence model to assist radiologists in interpreting X-ray images and generating reports, with the aim of improving diagnostic accuracy and reducing interpretation time.

Key facts

Study ID

NCT07497243

Run by

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

People needed

16000

Starts

2026-05-01

Expected to finish

2026-11-30

Last updated by the study team

2026-03-27

Who can join

Age: any. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• 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)

You may not qualify if…

• Substandard X-ray image quality (including severe motion artifacts, over-/underexposure, or missing anatomical structures)
• Pregnant or lactating women

Where it is running

• Wuhan Union Hospital — Wuhan, Hubei, China
• Wuhan Union Jinyin Lake Hospital — Wuhan, Hubei, China
• Wuhan Union West Hospital — Wuhan, Hubei, China
• The First Affiliated Hospital of Zhengzhou University — Zhengzhou, China

Full record on ClinicalTrials.gov

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