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. 2020 Mar 5;8(3):e15931. doi: 10.2196/15931

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©Chin-Sheng Lin, Chin Lin, Wen-Hui Fang, Chia-Jung Hsu, Sy-Jou Chen, Kuo-Hua Huang, Wei-Shiang Lin, Chien-Sung Tsai, Chih-Chun Kuo, Tom Chau, Stephen JH Yang, Shih-Hua Lin. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.03.2020.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.

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Visualization analysis for ECG12Net-1 in selected severe hypokalemia and hyperkalemia cases. The lighter areas (green or yellow) indicate areas of focus by ECG12Net-1. Clinicians consistently recognized panel A as a typical case of severe hypokalemia but overlooked panel B. Similarly, clinicians consistently recognized panel C as severe hyperkalemia but overlooked panel D. From A to D, the real K⁺ concentrations were 2.3 mEq/L, 2.5 mEq/L, 9.1 mEq/L, and 7.1 mEq/L, respectively. AI: artificial intelligence.