Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within the medical community, and specifically within the domain of cardiovascular diseases. In this review, we present a brief overview of ML methodologies that are used for the construction of inferential and predictive data-driven models. We highlight several domains of ML application such as echocardiography, electrocardiography, and recently developed non-invasive imaging modalities such as coronary artery calcium scoring and coronary computed tomography angiography. We conclude by reviewing the limitations associated with contemporary application of ML algorithms within the cardiovascular disease field.
Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging / S.J. Al'Aref, K. Anchouche, G. Singh, P.J. Slomka, K.K. Kolli, A. Kumar, M. Pandey, G. Maliakal, A.R. van Rosendael, A.N. Beecy, D.S. Berman, J. Leipsic, K. Nieman, D. Andreini, G. Pontone, U.J. Schoepf, L.J. Shaw, H. Chang, J. Narula, J.J. Bax, Y. Guan, J.K. Min. - In: EUROPEAN HEART JOURNAL. - ISSN 1522-9645. - 40:24(2019 Jun 21), pp. 1975-1986. [10.1093/eurheartj/ehy404]
Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging
D. Andreini;G. Pontone;
2019
Abstract
Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within the medical community, and specifically within the domain of cardiovascular diseases. In this review, we present a brief overview of ML methodologies that are used for the construction of inferential and predictive data-driven models. We highlight several domains of ML application such as echocardiography, electrocardiography, and recently developed non-invasive imaging modalities such as coronary artery calcium scoring and coronary computed tomography angiography. We conclude by reviewing the limitations associated with contemporary application of ML algorithms within the cardiovascular disease field.File | Dimensione | Formato | |
---|---|---|---|
clinical applications.pdf
accesso riservato
Descrizione: Review
Tipologia:
Publisher's version/PDF
Dimensione
772.73 kB
Formato
Adobe PDF
|
772.73 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.