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Artificial intelligence may detect Children's heart disease from a routine ECG

NCT ID NCT06383546

Terminated Diagnosis Sponsor: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine Source: ClinicalTrials.gov ↗

First seen Jul 29, 2026 · Last updated Jul 30, 2026 · Updated 1 time

Summary

This trial is developing an artificial intelligence system that reads electrocardiograms (ECGs) to detect congenital heart disease in children. Researchers are collecting ECG data from thousands of children, including those with common and rare heart defects, to train a deep-learning model. The goal is to create a fast, affordable screening tool that could help catch heart problems earlier, especially in settings where advanced imaging is not readily available.

What this could mean

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

Active substance
an artificial intelligence system that analyzes electrocardiograms (ECGs) to detect congenital heart disease in children
What this could lead to
If it works, this could provide a fast, low-cost screening tool to catch congenital heart disease earlier in children, potentially improving outcomes and reducing mortality.
What could go wrong
This is an early-stage study focused on building and testing the AI model, not a large clinical trial. The system may not perform well across all types of heart defects or in real-world settings.

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.

atrial septal defect congenital heart disease disease pulmonary arterial hypertension

As listed by the trial registrant

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

ARTIFICIAL INTELLIGENCE CONGENITAL HEART DISEASE IN CHILDREN DEEP LEARNING DIAGNOSIS ELECTROCARDIOGRAM

Contacts and locations

Locations

  • Xinhua Hospital, Shanghai Jiao Tong University School of Medicine

    Shanghai, Shanghai Municipality, China

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