Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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pp. 393-404
S&M2462 Research Paper of Special Issue

Prediction of Atrial Fibrillation Cases: Convolutional Neural Networks Using the Output Texts of Electrocardiography

Tak-Sung Heo, Chulho Kim, Jong-Dae Kim, Chan-Young Park, and Yu-Seop Kim

(Received June 30, 2020; Accepted November 24, 2020)

Keywords: atrial fibrillation, electrocardiogram, FastText, convolutional neural networks, prediction

Atrial fibrillation (AF) is the most common arrhythmia. Since AF can cause strokes if it lasts for a long time, it is important to detect AF in advance and receive treatment. Electrocardiography is usually used for AF diagnosis. Electrocardiography records the electrical activity of the patient’s heart to obtain an electrocardiogram (ECG), which usually consists of waves and a commentary on them. The onset of AF occurrence or its likelihood is judged by a comprehensive analysis of an ECG, which requires considerable prior knowledge and clinical experience. In this study, to make this process simpler, the output text of ECGs is analyzed by deep learning to predict the possibility of future AF. The proposed model represents words as vectors using FastText, and extracts features using one-dimensional convolutional neural networks. The model also combines features using global average pooling and is trained to calculate the probability of developing AF. In an experiment, the model showed 85.03% accuracy in predicting the presence or absence of AF. We thus demonstrated the possibility of predicting the occurrence of AF in advance using only text analysis without prior knowledge and clinical experience of AF.

Corresponding author: Yu-Seop Kim




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