New Open-Source AI aims to speed up chest X-Ray reports

NCT ID NCT07117266

First seen Jun 24, 2026 · Last updated Jun 26, 2026 · Updated 1 time

Summary

This study tested a new AI system (Janus Pro 1B-CXR) designed to help radiologists interpret chest X-rays. The AI was developed using public data and evaluated in 296 patients with suspected chest diseases. Researchers compared report quality, reading time, and agreement between junior radiologists using the AI and those working without it. The goal is to see if this low-cost, open-source AI can improve efficiency and accuracy in clinical practice, especially in areas with a shortage of radiologists.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance
AI system (Janus Pro 1B-CXR) for chest X-ray interpretation
What this could lead to
If successful, this AI could help radiologists work faster and more accurately, especially in areas with few specialists, potentially improving diagnosis of chest diseases like pneumonia or lung cancer.
What could go wrong
This is a small, completed study (296 participants) testing a new AI model. The AI may not perform as well in real-world settings or with different patient groups, and it hasn't been compared to other advanced AI systems in routine practice.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Locations

  • The First Affiliated Hospital of Henan University of science and technology

    Luoyang, 471003, China

  • The First Affiliated Hospital of Zhengzhou University

    Zhengzhou, 450002, China

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

    Wuhan, 430023, China

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