Artificial intelligence-assisted diagnosis and prognostication in low ejection fraction using electrocardiograms in inpatient department: a pragmatic randomized controlled trial

Abstract Background Early diagnosis of low ejection fraction (EF) remains challenging despite being a treatable condition. This study aimed to evaluate the effectiveness of an electrocardiogram (ECG)-based artificial intelligence (AI)-assisted clinical decision support tool in improving the early di...

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Autors principals:	Dung-Jang Tsai, Chin Lin, Wei-Ting Liu, Chiao-Chin Lee, Chiao-Hsiang Chang, Wen-Yu Lin, Yu-Lan Liu, Da-Wei Chang, Ping-Hsuan Hsieh, Chien-Sung Tsai, Yuan-Hao Chen, Yi-Jen Hung, Chin-Sheng Lin
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2025-06-01
Col·lecció:	BMC Medicine
Matèries:	Artificial intelligence Electrocardiogram Rapid response systems Low Ejection Fraction Randomized clinical trial High-intensity care
Accés en línia:	https://doi.org/10.1186/s12916-025-04190-z
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