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Cardiovascular, Digital health & Informatics
ROMIAE (Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis) trial study protocol: a prospective multicenter observational study for validation of a deep learning–based 12-lead electrocardiogram analysis model for detecting acute myocardial infarction in patients visiting the emergency department
Tae Gun Shin, Youngjoo Lee, Kyuseok Kim, Min Sung Lee, Joon-myoung Kwon, on behalf of the ROMIAE study group
Clin Exp Emerg Med. 2023;10(4):438-445.   Published online November 28, 2023
DOI: https://doi.org/10.15441/ceem.22.360
                           Web of Science 3  Crossref 3
Digital health & Informatics
Explainable artificial intelligence in emergency medicine: an overview
Yohei Okada, Yilin Ning, Marcus Eng Hock Ong
Clin Exp Emerg Med. 2023;10(4):354-362.   Published online November 28, 2023
DOI: https://doi.org/10.15441/ceem.23.145
                           Web of Science 11  Crossref 14
Critical Care, Digital health & Informatics
Current challenges in adopting machine learning to critical care and emergency medicine
Cyra-Yoonsun Kang, Joo Heung Yoon
Clin Exp Emerg Med. 2023;10(2):132-137.   Published online May 15, 2023
DOI: https://doi.org/10.15441/ceem.23.041
                           Web of Science 8  Crossref 9
Cardiovascular, Digital health & Informatics
Interethnic validation of electrocardiogram image analysis software for detecting left ventricular dysfunction in an emergency department population
Haemin Lee, Woon Yong Kwon, Kyoung Jun Song, You Hwan Jo, Joonghee Kim, Youngjin Cho, Ji Eun Hwang, Yeongho Choi
Received October 22, 2024     Accepted January 8, 2025     Published online April 30, 2025
DOI: https://doi.org/10.15441/ceem.24.342    
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