AI learns to detect lung problems by listening to breath sounds

NCT ID NCT07227376

Recruiting now Knowledge-focused Sponsor: Eko Devices, Inc. Source: ClinicalTrials.gov ↗

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study uses digital stethoscopes to record lung sounds from 250 adults and children in real clinical settings. The goal is to train an artificial intelligence algorithm to automatically detect wheezes, crackles, and other abnormal sounds. The research does not test any treatment but aims to improve how lung diseases are diagnosed.

What this could mean

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

Active substance: Eko digital stethoscopes (CORE 500 and 3M Littmann CORE)
What this could lead to: If successful, this could lead to an AI tool that helps doctors quickly identify lung problems by listening to breath sounds.
What could go wrong: This is an early data-collection study, not a treatment trial. The AI algorithm may not perform well enough for real-world use, and results may not apply to all patients.

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.

lung disorder Respiratory Sounds

As listed by the trial registrant

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

LUNG DISEASES

Contacts and locations

Locations

Jefferson Einstein Philadelphia Hospital
RECRUITING

Philadelphia, Pennsylvania, 19141, United States
Nemours Children's Health
RECRUITING

Jacksonville, Florida, 32256, United States

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