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X-ray Assisted Diagnostic System
Sponsor: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Summary
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.
Official title: Construction and Clinical Application of an X-ray AI-Aided Diagnosis System: A Randomized Controlled Trial
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
16000
Start Date
2026-05-01
Completion Date
2026-11-30
Last Updated
2026-03-27
Healthy Volunteers
Yes
Conditions
Interventions
AI-assisted radiologist diagnostic group
Based on the previously developed X-ray image diagnosis and report generation model, radiologists are assisted in interpreting X-ray images and generating reports.
Radiologist diagnostic group
After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.
Locations (4)
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