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AI stethoscope aims to spot hidden heart and lung problems in children

NCT ID NCT06542120

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now This study
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Aug 12, 2026 · Last updated Aug 13, 2026 · Updated 1 time

Summary

This trial is developing an AI-powered device that listens to children's heart, breath, and bowel sounds to identify signs of common diseases like congenital heart disease, bronchopneumonia, and abdominal issues. It will involve 30,000 children aged 0-18, some with these conditions and some without, to test how accurately the AI can distinguish between normal and abnormal sounds. The goal is to create a non-invasive screening tool that could help with early detection and auxiliary diagnosis.

What this could mean

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

Active substance
AI-assisted body sound identification device using deep learning
What this could lead to
If successful, this could lead to a simple, non-invasive AI tool for early screening of common childhood diseases, potentially improving outcomes through earlier detection.
What could go wrong
The AI's accuracy is still being tested, and it may not perform consistently across all children or conditions. It is not a replacement for standard diagnostic tests.

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

Study facts

What this study's own registry entry says, in plain language.

Participants

About 30,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

May 2024

Expected to finish

Dec 2026

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

1. Children (0-18 years old) with congenital heart disease confirmed by cardiac ultrasound and children without congenital heart disease confirmed by cardiac ultrasound. 2. Children (0-18 years old) with bronchopneumonia confirmed by chest imaging examination and children without bronchopneumonia confirmed by imaging. 3. Children (0-18 years old) with abdominal imaging confirmed abdominal disease and children diagnosed without abdominal disease by imaging.

Ages

Up to 18 years

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: 1. Age 0\~18 years old, gender is not limited 2. Children who have been diagnosed with congenital heart disease by cardiac ultrasound or who do not have congenital heart disease 3. Children diagnosed with bronchopneumonia or without bronchopneumonia 4. Children who are clinically diagnosed with intestinal diseases or who do not suffer from intestinal diseases 5. Informed consent Exclusion Criteria: 1. ≥ 18 years old 2. Children who are unable to undergo cardiac ultrasound, chest imaging or other related examinations 3. Subjects who are unable to obtain informed consent, or who are unwilling to cooperate with the provision of diagnosis and treatment related data for further analysis and research as required by the study.

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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.

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    5 sites. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Human Children's Hospital

    RECRUITING

    Changsha, Hunan, 410007, China

  • Kunming children's Hospital

    RECRUITING

    Kunming, Yunnan, 650028, China

  • Shanghai Children's Medical Center Affiliated to Shanghai Jiaotong University School of Medicine

    RECRUITING

    Shanghai, Shanghai Municipality, 200127, China

  • Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology

    RECRUITING

    Wuhan, Hubei, 430016, China

  • Xinhua Hospital,Shanghai Jiao Tong University School of Medicine

    RECRUITING

    Shanghai, Shanghai Municipality, 200092, China

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