A Deep-Learning Algorithm (ECG12Net) for Detecting Hypokalemia and Hyperkalemia by Electrocardiography: Algorithm Development

The detection of dyskalemias-hypokalemia and hyperkalemia-currently depends on laboratory tests. Since cardiac tissue is very sensitive to dyskalemia, electrocardiography (ECG) may be able to uncover clinically important dyskalemias before laboratory results. Our study aimed to develop a deep-learni...

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Bibliographic Details
Published in:	JMIR medical informatics Vol. 8; no. 3; p. e15931
Main Authors:	Lin, Chin-Sheng, Lin, Chin, Fang, Wen-Hui, Hsu, Chia-Jung, Chen, Sy-Jou, Huang, Kuo-Hua, Lin, Wei-Shiang, Tsai, Chien-Sung, Kuo, Chih-Chun, Chau, Tom, Yang, Stephen JH, Lin, Shih-Hua
Format:	Journal Article
Language:	English
Published:	Canada JMIR Publications 01.03.2020
Subjects:	Accuracy Algorithms Cardiology Competition Deep learning Electrocardiography Hyperkalemia Hypokalemia Laboratories Morphology Original Paper Patients Performance evaluation Physicians electrocardiogram sudden cardiac death machine learning potassium homeostasis artificial intelligence
ISSN:	2291-9694, 2291-9694
Online Access:	Get full text
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