Semi-Supervised Recurrent Variational Autoencoder Approach for Visual Diagnosis of Atrial Fibrillation

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2021Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Access, volume 9, pages 40,227-40,239 (eissn: 2169-3536,

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Authors: Nahuel Costa; Luciano Sanchez; Ines Couso;

doi: 10.1109/access.2021.3064854

handle: 10651/60152

Semi-Supervised Recurrent Variational Autoencoder Approach for Visual Diagnosis of Atrial Fibrillation

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Abstract

This work was supported in part by the Ministry of Economy, Industry and Competitiveness (Ministerio de Economía, Industria y Competitividad) of Spain/FEDER under Grant TIN2017-84804-R and Grant PID2020-112726-RB.

Related Organizations

University of Oviedo
Spain

Keywords

recurrent neural networks, variational autoencoder, heart disease, Electrical engineering. Electronics. Nuclear engineering, time series, Graphical Analysis, TK1-9971

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