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To review current machine learning methodologies and their clinical applications in cardiovascular diagnostics and cardiac imaging.

July 7, 2018European Heart JournalOpen Access

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging

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To review current machine learning methodologies and their clinical applications in cardiovascular diagnostics and cardiac imaging.
Reviewed inferential and predictive machine learning techniques applied in cardiovascular medicine.
Evaluated machine learning integration across echocardiography, electrocardiography, coronary artery calcium scoring, and coronary computed tomography angiography.
Identified growing diagnostic utility of machine learning algorithms for pattern recognition in echocardiography and electrocardiography.
Demonstrated expanded applications of predictive modeling in advanced non-invasive imaging, such as coronary computed tomography angiography and calcium scoring.
Identified ongoing methodological and clinical limitations that restrict contemporary implementation of machine learning in cardiovascular care.

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Extends ML applications in echocardiography and ECG; leaves open prospective validation before clinical adoption.

Al’Aref et al. (2018) studied this question.

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