September 5, 2025Open HeartOpen Access

Machine learning to predict high-risk coronary artery disease on CT in the SCOT-HEART trial

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Observational analysis shows improved CAD prediction in 1769 patients, highlighting machine learning's potential benefits.

Machine learning predicted the presence of coronary artery disease on CT better than the 10-year cardiovascular risk score.
The model's area under the curve for CAD prediction was 0.80, significantly higher than the cardiovascular risk score's 0.75.
Machine learning was trained using data on symptoms, demographics, and clinical characteristics from the SCOT-HEART trial.
Although effective for CAD, the model could not significantly improve the prediction of low-attenuation coronary artery plaque burden.

Williams et al. (2025) studied this question.

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September 5, 2025Open HeartOpen Access

View Full Paper

Ask AI

Bookmark

Authors

Observational analysis shows improved CAD prediction in 1769 patients, highlighting machine learning's potential benefits.

Machine learning predicted the presence of coronary artery disease on CT better than the 10-year cardiovascular risk score.
The model's area under the curve for CAD prediction was 0.80, significantly higher than the cardiovascular risk score's 0.75.
Machine learning was trained using data on symptoms, demographics, and clinical characteristics from the SCOT-HEART trial.
Although effective for CAD, the model could not significantly improve the prediction of low-attenuation coronary artery plaque burden.

Williams et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark