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NOT YET RECRUITING
NCT07179185
NA

Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs

Sponsor: Federal University of Minas Gerais

View on ClinicalTrials.gov

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

DIAGNOSTIC_TEST

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.

DIAGNOSTIC_TEST

Specialist ECG Interpretation Without AI

Manual interpretation of ECGs by specialists without AI support, following standard diagnostic procedures