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Frontiers in Cardiovascular Medicine logoLink to Frontiers in Cardiovascular Medicine
. 2022 Dec 9;9:1078223. doi: 10.3389/fcvm.2022.1078223

Corrigendum: Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care

Ke-Wei Chen 1,2,, Yu-Chen Wang 1,3,4,, Meng-Hsuan Liu 5, Being-Yuah Tsai 5, Mei-Yao Wu 6,7, Po-Hsin Hsieh 8, Jung-Ting Wei 1,9, Edward S C Shih 10, Yi-Tzone Shiao 11, Ming-Jing Hwang 10, Ya-Lun Wu 5, Kai-Cheng Hsu 5, Kuan-Cheng Chang 1,9,*
PMCID: PMC9780667  PMID: 36568545

In the original article, there was an error in Figure 1: “The flowchart of the AI-based pre-hospital STEMI detection system” as published. A typo error in the figure read “Prehospital 12-lead ECG examinectin,” and has been corrected to “Prehospital 12-lead ECG examination.” The corrected figure appears below.

Figure 1.

Figure 1

The flowchart of the AI-based pre-hospital STEMI detection system. Traditionally, after the 12-lead ECG had been recorded in the ambulance vehicle, the ECG data were posted on a secured network for reading by available online physicians as had been usual practice. The time interval between ECG transmission and interpretation feedback by physicians was defined as the physician's response time. In our AI-based pre-hospital STEMI detection system, the recorded signal was also simultaneously transmitted to the AI center of the China Medical University Hospital to be classified “STEMI” or “Not STEMI.” Similarly, the time interval between the ECG transmission and the ECG interpretation feedback by the AI was defined as the AI's response time.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

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