Machine Learning in Electrocardiography and Echocardiography: Technological Advances in Clinical Cardiology
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cardiology and Cardiovascular Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11886-020-01416-9.pdf
Reference58 articles.
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3. • Ribeiro AH, Ribeiro MH, Paixão GMM, Oliveira DM, Gomes PR, Canazart JA, et al. Automatic diagnosis of the 12-lead ECG using a deep neural network. Nat Comm. 2020;11(1). https://doi.org/10.1038/s41467-020-15432-4This study used a very large dataset to create a DNN that matches or outperformed medical students/residents in detecting conduction abnormalities when compared on a multitude of ECG tracings.
4. Knackstedt C, Bekkers SCAM, Schummers G, Schreckenberg M, Muraru D, Badano LP, et al. Fully automated versus standard tracking of left ventricular ejection fraction and longitudinal strain. J Am Coll Cardiol. 2015;66(13):1456–66. https://doi.org/10.1016/j.jacc.2015.07.052.
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