bioRxiv (Cold Spring Harbor Laboratory)
Automated diagnosis of atrial fibrillation in 24-hour Holter recording based on deep learning:a study with randomized and real-world data validation
August 2021 • Peng Zhang, Fan Lin, Fei Ma, Yuting Chen, Dao Wen Wang, Xiaoyun Yang, Qiang Li
Summary Background With the increasing demand for atrial fibrillation (AF) screening, clinicians spend a significant amount of time in identifying the AF signals from massive electrocardiogram (ECG) data in long-term dynamic ECG monitoring. In this study, we aim to reduce clinicians’ workload and promote AF screening by using artificial intelligence (AI) to automatically detect AF episodes and identify AF patients in 24 h Holter recording. Methods We used a total of 22 979 Holter recordings (24 h) from 22 757 adul…