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- W4313557144 abstract "The rapid identification of cardiac implanted electronic devices (CIEDs) is important in several clinical settings. Computer vision applications based on convolutional neural networks (CNNs) have been applied widely in cardiac imaging, and these methods have also been used to identify CIEDs on chest radiographs (CXRs). 1 Chudow J.J. Jones D. Weinreich M. et al. A head-to head comparison of machine learning algorithms for identification of implanted cardiac devices. Am J Cardiol. 2021; 144: 77-82 Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar , 2 Howard J.P. Fisher L. Shun-Shin M.J. et al. Cardiac rhythm device identification using neural networks. JACC Clin Electrophysiol. 2019; 5: 576-586 Crossref PubMed Scopus (36) Google Scholar , 3 Kim U.-H. Kim M.Y. Park E.-A. et al. Deep learning-based algorithm for the detection and characterization of MRI safety of cardiac implantable electronic devices on chest radiographs. Korean J Radiol. 2021; 22: 1918 Crossref PubMed Scopus (2) Google Scholar , 4 Weinreich M. Chudow J.J. Weinreich B. et al. Development of an artificially intelligent mobile phone application to identify cardiac devices on chest radiography. JACC Clin Electrophysiol. 2019; 5: 1094-1095 Crossref PubMed Scopus (9) Google Scholar However, previously published studies are limited by the small scale of data sets." @default.
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- W4313557144 date "2023-04-01" @default.
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- W4313557144 title "Detection and identification of cardiac implanted electronic devices in a large data set of chest radiographs using semi-supervised artificial intelligence methods" @default.
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- W4313557144 doi "https://doi.org/10.1016/j.hrthm.2022.12.038" @default.
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