Author Correction: Automatic diagnosis of the 12-lead ECG using a deep neural network

Author:

Ribeiro Antônio H.ORCID,Ribeiro Manoel Horta,Paixão Gabriela M. M.,Oliveira Derick M.,Gomes Paulo R.,Canazart Jéssica A.,Ferreira Milton P. S.,Andersson Carl R.,Macfarlane Peter W.,Meira Wagner,Schön Thomas B.ORCID,Ribeiro Antonio Luiz P.ORCID

Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

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1. Breaking Barriers in Stress Detection: An Inter-Subject Approach Using ECG Signals;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

2. Early prediction of sudden cardiac death risk with Nested LSTM based on electrocardiogram sequential features;BMC Medical Informatics and Decision Making;2024-04-10

3. Cardiac Health Monitoring with Machine Learning: ECG-Based Disease Detection;International Journal of Advanced Research in Science, Communication and Technology;2024-03-18

4. IM-ECG: An interpretable framework for arrhythmia detection using multi-lead ECG;Expert Systems with Applications;2024-03

5. Validation of an automated artificial intelligence system for 12‑lead ECG interpretation;Journal of Electrocardiology;2024-01

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