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Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs
Sponsor: Federal University of Minas Gerais
Summary
This study will evaluate the performance of specialist physicians in interpreting normal electrocardiograms (ECGs) with and without the assistance of an artificial intelligence (AI) neural network. The primary aim is to determine whether AI support affects the rate of false-positive interpretations of normal tracings. Secondary aims include evaluating the time required for interpretation, the sensitivity for detecting abnormalities, and the effect on false positives in ECGs with major abnormalities according to the Minnesota Code system. All ECGs in the sample will be reviewed by a panel of three specialists, to determine the reference classification.
Official title: PRECISE-ECG: Prospective Randomized Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
710
Start Date
2025-10-01
Completion Date
2025-11
Last Updated
2025-09-22
Healthy Volunteers
No
Interventions
AI-Assisted ECG Interpretation (AI-ECG)
Neural network-based AI software that analyzes ECG tracings and provides a classification as normal suggestion to the interpreting specialist.
Specialist ECG Interpretation Without AI
Manual interpretation of ECGs by specialists without AI support, following standard diagnostic procedures