Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals-Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study.
Changho HanYoungjae SongHong Seok LimYunwon TaeJong Hwan JangByeong Tak LeeYeha LeeWoong BaeDukyong YoonPublished in: Journal of medical Internet research (2021)
By developing an AI model for detecting acute myocardial infarction with asynchronous ECG lead sets, we demonstrated the feasibility of multiple lead-based AI-enabled ECG algorithms on smartwatches for automated diagnosis of cardiac disorders. We also demonstrated the necessity of measuring at least 3 leads for accurate detection. Our results can be used as reference for the development of other AI models using sequentially measured asynchronous ECG leads via smartwatches for detecting various cardiac disorders.
Keyphrases
- artificial intelligence
- machine learning
- acute myocardial infarction
- deep learning
- left ventricular
- big data
- heart rate variability
- heart rate
- percutaneous coronary intervention
- loop mediated isothermal amplification
- label free
- real time pcr
- heart failure
- coronary artery disease
- high resolution
- blood pressure
- mass spectrometry
- single cell