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AI learns to read Children's breathing in the ER

NCT ID NCT07370623

First seen Jan 27, 2026 · Last updated Jun 20, 2026 · Updated 25 times

Summary

This study is collecting data from 2,200 children aged 0 to 12 who come to emergency rooms with breathing problems. Researchers will use videos and clinical information to train an artificial intelligence system to automatically recognize different breathing patterns. The goal is to create a tool that helps doctors assess respiratory distress more objectively and quickly.

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This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.

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Contacts and locations

Locations

  • Asan Medical Center, 88, Olympic-ro 43-gil, Songpa-gu

    RECRUITING

    Seoul, Seoul, 05505, South Korea

    Contact Phone: •••-•••-•••• Email: •••••@•••••

  • CHA Bundang Medical Center, CHA University, 9, Yatap-ro, Bundang-gu

    RECRUITING

    Seongnam-si, Gyeonggi-do, 13496, South Korea

    Contact Phone: •••-•••-•••• Email: •••••@•••••

  • Samsung Medical Center, 81, Irwon-ro, Gangnam-gu

    RECRUITING

    Seoul, Seoul, 06351, South Korea

    Contact Phone: •••-•••-•••• Email: •••••@•••••

What this could mean

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

What this could lead to

If successful, this could lead to an AI tool that helps doctors quickly and objectively assess breathing problems in children, potentially improving emergency care.

What could go wrong

This is an early observational study focused on data collection and AI development, not a treatment trial. The AI system may not perform accurately enough for real-world use, and results may not apply to all hospitals.

As listed by the trial registrant

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