An interventional study of AI-Assisted ECG Interpretation (AI-ECG) and Specialist ECG Interpretation Without AI in Electrocardiogram and Cardiovascular Abnormalities, sponsored by Federal University of Minas Gerais. Not yet recruiting. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-09-22.
Sponsored by Federal University of Minas Gerais · Not applicable, Interventional, and Diagnostic
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.
59 studies on the registry are indexed under Cardiovascular Abnormalities; 14 are open to participants now.
This study's planned enrollment of 710 is above the median of 60 across 33 interventional studies indexed under Cardiovascular Abnormalities.
Browse Cardiovascular Abnormalities studies →Federal University of Minas Gerais is the lead sponsor of 150 studies on the registry; 18 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Specialist physicians interpret normal ECGs without the assistance of the AI-ECG tool. ECGs are routine tracings performed by the Rede de Telemedicina de Minas Gerais (RTMG). Final classification for study endpoints will be based on a panel review by three specialists.
Diagnostic Test: Specialist ECG Interpretation Without AI
Specialist physicians interpret ECGs using the AI-ECG tool, which provides automated classification support indicating whether the ECG is normal or not. ECGs are routine tracings performed by RTMG. Final classification for study endpoints will be based on a panel review by three specialists.
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.
Manual interpretation of ECGs by specialists without AI support, following standard diagnostic procedures
Precision (Positive Predictive Value) for detection of normal ECG tracings
Precision (Positive Predictive Value) of detecting normal ECG by the physician or physician+model compared against the reference standard defined by a panel of three specialists. Precision (Positive Predictive Value) is defined by the number of true positive normal cases divided by all positive predictions.
Time frame: One week
Sensitivity, Specificity, Negative Predictive Value, and F1 score for detection of normal ECG tracings
Accuracy evaluated by Sensitivity, Specificity, Negative Predictive Value, and F1 score of normal ECGs correctly identified by the physician or physician+model, in relation to a reference standard defined by a panel of three specialists.
Time frame: One week
ECGs with major abnormalities incorrectly classified as normal
Ratio of ECGs with major abnormalities according to the Minnesota Code system among those incorrectly classified as normal by the physician or physician+model, in relation to a reference standard defined by a panel of three specialists.
Time frame: One week
Time of analysis for normal cases (seconds per case)
Time required by the physician, or physician+model, to interpret normal ECGs, measured in seconds per case; the reference standard of normal cases defined by a panel of three specialists.
Time frame: One week
No study locations are listed for this record.
Plan to share: No
This study is not yet recruiting, as verified in Sep 2025. You cannot join it, but the record below documents what was studied.
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Federal University of Minas Gerais