Research and Application of Artificial Intelligence in Atrial Fibrillation
Atrial fibrill ation,as the most common persistent arrhythmia worldwide,poses a significant economic burden to public health systems due to its high morbidity and mortality.Early detection of atrial fibrillation is essential for timely treatment and prevention of complications such as stroke.Although 12-lead ECG is the gold standard for diagnosing atrial fibrillation,it relies on the clinical experience of a cardiologist and may be affected by inter-observer variability.Artificial intelligence(AI),especially convolutional neural networks(CNNs)in deep learning(DL),have made significant progress in image recognition tasks,enabling the automated evaluation of complex medical images with greater accuracy and efficiency.The purpose of this article is to provide a comprehensive overview of AI technology and explore its potential for research and clinical application in atrial fibrillation.
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