Peek: A Cloud-Based Application for Automatic´ Electrodiogram Pre-Diagnosis

Medientyp: E-Book

Titel: Peek : A Cloud-Based Application for Automatic´ Electrodiogram Pre-Diagnosis

Beteiligte: Zermeño Campos, Nestor [VerfasserIn]; Cuevas Gonzalez, Daniel [VerfasserIn]; Garcia-Vazquez, Juan Pablo [VerfasserIn]; Zanoguera, Miguel E. Bravo [VerfasserIn]; Avitia, Roberto López [VerfasserIn]; Reyna-Carranza, Marco A. [VerfasserIn]; Díaz Ramirez, Arnoldo [VerfasserIn]

Erschienen: [S.l.]: SSRN, [2022]

Umfang: 1 Online-Ressource (11 p)

Sprache: Englisch

DOI: 10.2139/ssrn.4017404

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Beschreibung: Electrocardiogram (ECG) visual analysis and interpretation is a common task performed by a healthcare specialist as a cardiovascular-diseases prediagnostic technique. However, when an ECG specialist must analyze a longtime duration record such as a 24-hour Holter; this task becomes not only a tiresome and complicated but also a very probable erroneous diagnostic. In this article, we present a cloud-based application called PEEK that helps´ healthcare specialists automatically detect normal and abnormal beats on ECG registers using Convolutional Neural Networks (CNN). To illustrate the functionality of PEEK, we present the analysis of an ECG register from´ the MIT-BIH Arrhythmia Database. The software can detect normal heart beats and premature ventricular contractions (PVC) beats with a 98.93% of accuracy

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