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Design and use of a Denoising Convolutional Autoencoder for reconstructing electrocardiogram signals at super resolution.

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Title: Design and use of a Denoising Convolutional Autoencoder for reconstructing electrocardiogram signals at super resolution.
Authors: Lomoio U; Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Italy. Electronic address: ugo.lomoio@unicz.it., Veltri P; DIMES, University of Calabria, Rende, Italy. Electronic address: pierangelo.veltri@dimes.unical.it., Guzzi PH; Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Italy. Electronic address: hguzzi@unicz.it., Liò P; Department of Computer Science and Technology, Cambridge University, Cambridge, United Kingdom. Electronic address: pl219@cam.ac.uk.
Source: Artificial intelligence in medicine [Artif Intell Med] 2025 Feb; Vol. 160, pp. 103058. Date of Electronic Publication: 2024 Dec 28.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Elsevier Science Publishing Country of Publication: Netherlands NLM ID: 8915031 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2860 (Electronic) Linking ISSN: 09333657 NLM ISO Abbreviation: Artif Intell Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Design and use of a Denoising Convolutional Autoencoder for reconstructing electrocardiogram signals at super resolution.
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  Data: <searchLink fieldCode="AU" term="%22Lomoio+U%22">Lomoio U</searchLink>; Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Italy. Electronic address: ugo.lomoio@unicz.it.<br /><searchLink fieldCode="AU" term="%22Veltri+P%22">Veltri P</searchLink>; DIMES, University of Calabria, Rende, Italy. Electronic address: pierangelo.veltri@dimes.unical.it.<br /><searchLink fieldCode="AU" term="%22Guzzi+PH%22">Guzzi PH</searchLink>; Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Italy. Electronic address: hguzzi@unicz.it.<br /><searchLink fieldCode="AU" term="%22Liò+P%22">Liò P</searchLink>; Department of Computer Science and Technology, Cambridge University, Cambridge, United Kingdom. Electronic address: pl219@cam.ac.uk.
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  Data: <searchLink fieldCode="JN" term="%228915031%22">Artificial intelligence in medicine</searchLink> [Artif Intell Med] 2025 Feb; Vol. 160, pp. 103058. <i>Date of Electronic Publication: </i>2024 Dec 28.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Science+Publishing%22">Elsevier Science Publishing </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>8915031 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1873-2860 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2209333657%22">09333657 </searchLink><i>NLM ISO Abbreviation: </i>Artif Intell Med <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.artmed.2024.103058
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      – Code: eng
        Text: English
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      – TitleFull: Design and use of a Denoising Convolutional Autoencoder for reconstructing electrocardiogram signals at super resolution.
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              Text: 2025 Feb
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              Y: 2025
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