X-ray Assisted Diagnostic System
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI-assisted radiologist diagnostic group, Radiologist diagnostic group.
- Who it may be relevant to
- Registry conditions: Chest X-ray for Clinical Evaluation. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Construction and Clinical Application of an X-ray AI-Aided Diagnosis System: A Randomized Controlled Trial
Overview
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.
Interventions
- Diagnostic test 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. - Diagnostic test Radiologist diagnostic group
After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.
Primary outcome measures
- Area Under the Curve [Time frame: From enrollment to the end of X-ray image acquisition at 1 week]
Secondary outcome measures (1)
- X-ray report generation time [Time frame: From enrollment to the end of X-ray image acquisition at 1 week]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Case-control
Study locations
China · 4 centers
- Wuhan Union Hospital — Wuhan
- Wuhan Union Jinyin Lake Hospital — Wuhan
- Wuhan Union West Hospital — Wuhan
- The First Affiliated Hospital of Zhengzhou University — Zhengzhou
Identifiers
NCT: NCT07497243 · X-Ray-001