1 Introduction According to the World Health Organization,heart disease has been the leading cause of death worldwide for the past 20 years.Electrocardiography(ECG or EKG)records the electrophysiological activity of t...1 Introduction According to the World Health Organization,heart disease has been the leading cause of death worldwide for the past 20 years.Electrocardiography(ECG or EKG)records the electrophysiological activity of the heart in time,allowing accurate diagnoses by clinicians[1].Despite the relative simplicity of ECG acquisition,its interpretation requires extensive training.Manual examination and re-examination of ECG paper records can be time-consuming,potentially delaying diagnosis.Machine learning,which uses algorithms to identify patterns within data and make predictive analyses,has played a significant role in interpreting ECGs[2].展开更多
基金supported by the NSFC-FDCT Grant 62361166662the National Key R&D Program of China(2023YFC3503400,2022YFC3400400)+4 种基金the Innovative Research Group Project of Hunan Province(2024JJ1002)the Key R&D Program of Hunan Province(2023GK2004,2023SK2059,2023SK2060)the Top 10 Technical Key Project in Hunan Province(2023GK1010)the Key Technologies R&D Program of Guangdong Province(2023B1111030004 to FFH)the Funds of the National Supercomputing Center in Changsha.
文摘1 Introduction According to the World Health Organization,heart disease has been the leading cause of death worldwide for the past 20 years.Electrocardiography(ECG or EKG)records the electrophysiological activity of the heart in time,allowing accurate diagnoses by clinicians[1].Despite the relative simplicity of ECG acquisition,its interpretation requires extensive training.Manual examination and re-examination of ECG paper records can be time-consuming,potentially delaying diagnosis.Machine learning,which uses algorithms to identify patterns within data and make predictive analyses,has played a significant role in interpreting ECGs[2].
