Health TrialsbyHealthPanel

X-ray Assisted Diagnostic System

ConditionChest X-ray for Clinical Evaluation
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
AgeNot listed
SponsorUnion Hospital, Tongji Medical College, Huazhong University of Science and Technology

About this trial

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.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

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)

Disqualifiers

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

Pregnant or lactating women

Trial population

Patients scheduled to undergo X-ray examination

Trial design

Design model

Case-control

Time perspective

Prospective

Treatments tested in this trial

  • AI-assisted radiologist diagnostic group

    Diagnostic test

    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

    Diagnostic test

    After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.

Treatment groups

16,000 Participants
are divided into 2 treatment groups
Group A: Radiologist diagnostic group1 intervention
Group B: AI-assisted radiologist diagnostic group1 intervention

Trial outcomes

Primary outcomes

1

Area Under the Curve

The primary outcome was the AUC to evaluate diagnostic performance, comparing radiologists with and without AI assistance.

Time frame
From enrollment to the end of X-ray image acquisition at 1 week

Secondary outcomes

1

X-ray report generation time

X-ray report generation time refers to the amount of time required to produce a diagnostic report after an X-ray examination has been performed. It typically measures the interval from when the X-ray images are acquired to when the radiologist (with or without AI assistance) completes and finalizes the report.

Time frame
From enrollment to the end of X-ray image acquisition at 1 week

Other outcomes

1

Radiologist score

Radiologist score refers to the evaluation or rating assigned by senior radiologists based on imaging findings generated by AI or AI+radiologist.

Time frame
From enrollment to the end of X-ray image acquisition at 4 weeks

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

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

Lead sponsor

Source ClinicalTrials.gov

This trial is not recruiting at the moment. You can still explore other options: