X-ray Assisted Diagnostic System

Condition(s) studied

Investigational drug(s) / intervention(s)

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.

Study 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.

Eligibility

Primary outcome measure(s)

• Area Under the Curve — From enrollment to the end of X-ray image acquisition at 1 week
  The primary outcome was the AUC to evaluate diagnostic performance, comparing radiologists with and without AI assistance.

Trial sites (4)

More Union Hospital, Tongji Medical College, Huazhong University of Science and Technology trials in China

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