Deep-learning algorithms can be applied to large datasets of electrocardiograms, are capable of identifying abnormal heart rhythms and mechanical dysfunction, and could aid healthcare decisions.
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References
Bycroft, C. et al. Nature 562, 203–209 (2018).
Hannun, A. Y. et al. Nat. Med. https://doi.org/10.1038/s41591-018-0268-3 (2019).
Attia, Z. I. et al. Nat. Med. https://doi.org/10.1038/s41591-018-0240-2 (2019).
Lau, J. K. et al. Int. J. Cardiol. 165, 193–194 (2013).
Lyon, A., Mincholé, A., Martínez, J. P., Laguna, P. & Rodriguez, B. J. R. Soc. Interface 15, 20170821 (2018).
Kiranyaz, S., Ince, T. & Gabbouj, M. IEEE Trans. Biomed. Eng. 63, 664–675 (2016).
Moody, G. B. & Mark, R. G. IEEE Eng. Med. Biol. Mag. 20, 45–50 (2001).
Lyon, A., Bueno-Orovio, A., Zacur, E., Ariga, R., Grau, V., Neubauer, S., Watkins, H., Rodriguez, B. & Mincholé, A. Europace 20, iii102–iii112 (2018).
Martínez, J. P., Almeida, R., Olmos, S., Rocha, A. P. & Laguna, P. IEEE Trans. Biomed. Eng. 51, 570–581 (2004).
Camps, J., McCarthy, A., Rodrıguez, B. & Minchole, A. Deep learning based QRS multilead delineator in electrocardiogram signals. In Proc. 3rd International Workshop on Biomedical Informatics with Optimization and Machine Learning (2018).
Bai, W. et al. J. Cardiovasc. Magn. Reson. 20, 65 (2018).
Goldberger, A. L. et al. Circulation 101, E215–E220 (2000).
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Mincholé, A., Rodriguez, B. Artificial intelligence for the electrocardiogram. Nat Med 25, 22–23 (2019). https://doi.org/10.1038/s41591-018-0306-1
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DOI: https://doi.org/10.1038/s41591-018-0306-1
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