What type of study is this?

This is a Meta-Analysis study (also classified as: Systematic Review).

August 16, 2025HeartsOpen Access

Machine Learning Application in Different Imaging Modalities for Detection of Obstructive Coronary Artery Disease and Outcome Prediction: A Systematic Review and Meta-Analysis

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Meta-analysis reviews machine learning's effectiveness in predicting clinical outcomes across imaging modalities for coronary artery disease.

Machine learning methods show promise in diagnosing coronary artery disease, achieving a combined c-index of 0.84 across various modalities.
Notable imaging modalities include coronary angiography, computed tomography, and nuclear stress imaging, with 46 studies analyzed.
Deep neural networks and convolutional neural networks were key models, indicating their popularity in machine learning applications.
High heterogeneity among studies raises concerns about standardization, emphasizing the need for consistent methodologies in future research.

McGranaghan et al. (2025) studied this question.

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August 16, 2025HeartsOpen Access

View Full Paper

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Authors

Meta-analysis reviews machine learning's effectiveness in predicting clinical outcomes across imaging modalities for coronary artery disease.

Machine learning methods show promise in diagnosing coronary artery disease, achieving a combined c-index of 0.84 across various modalities.
Notable imaging modalities include coronary angiography, computed tomography, and nuclear stress imaging, with 46 studies analyzed.
Deep neural networks and convolutional neural networks were key models, indicating their popularity in machine learning applications.
High heterogeneity among studies raises concerns about standardization, emphasizing the need for consistent methodologies in future research.

McGranaghan et al. (2025) studied this question.

Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context:

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