{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["46(20)"],"submitter":["Lee MS"],"pubmed_abstract":["Background and aims
Emerging evidence supports artificial intelligence-enhanced electrocardiogram (AI-ECG) for detecting acute myocardial infarction (AMI), but real-world validation is needed. The aim of this study was to evaluate the performance of AI-ECG in detecting AMI in the emergency department (ED).Methods
The Rule-Out acute Myocardial Infarction using Artificial intelligence Electrocardiogram analysis (ROMIAE) study is a prospective cohort study conducted in the Republic of Korea from March 2022 to October 2023, involving 18 university-level teaching hospitals. Adult patients presenting to the ED within 24 h of symptom onset concerning for AMI were assessed. Exposure included AI-ECG score, HEART score, GRACE 2.0 score, high-sensitivity troponin level, and Physician "],"journal":["European heart journal"],"pagination":["1917-1929"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12093146"],"repository":["biostudies-literature"],"pubmed_title":["Artificial intelligence applied to electrocardiogram to rule out acute myocardial infarction: the ROMIAE multicentre study."],"pmcid":["PMC12093146"],"pubmed_authors":["Son JM","Jeong JH","Shin N","Kim WY","Kim K","Choi K","Kim MY","Kwon JM","Choi J","Lim TH","Rhee B","Choi S","Kim WJ","Kim DW","Jeong KY","Lee HS","Cho H","Kim SE","Bu JH","Park SJ","Jang JH","Kim DH","Park JE","Ko SH","Cho Y","Min YG","Jung E","Jung H","Yoon JC","Kang S","Choi HS","Chung H","Shin TG","Ahn C","Kim JS","Choi SH","Lee MS","Seo JY","Kim JH","Lee Y","Han C","Ahn S","Jo YY","Lee MJ","ROMIAE study group"],"additional_accession":[]},"is_claimable":false,"name":"Artificial intelligence applied to electrocardiogram to rule out acute myocardial infarction: the ROMIAE multicentre study.","description":"Background and aims
Emerging evidence supports artificial intelligence-enhanced electrocardiogram (AI-ECG) for detecting acute myocardial infarction (AMI), but real-world validation is needed. The aim of this study was to evaluate the performance of AI-ECG in detecting AMI in the emergency department (ED).Methods
The Rule-Out acute Myocardial Infarction using Artificial intelligence Electrocardiogram analysis (ROMIAE) study is a prospective cohort study conducted in the Republic of Korea from March 2022 to October 2023, involving 18 university-level teaching hospitals. Adult patients presenting to the ED within 24 h of symptom onset concerning for AMI were assessed. Exposure included AI-ECG score, HEART score, GRACE 2.0 score, high-sensitivity troponin level, and Physician ","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 May","modification":"2026-04-08T19:00:37.272Z","creation":"2026-04-08T11:26:17.164Z"},"accession":"S-EPMC12093146","cross_references":{"pubmed":["39992309"],"doi":["10.1093/eurheartj/ehaf004"]}}