most citedReading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Reconstructing 12-Lead ECG from 3-Lead ECG using Variational Autoencoder to Improve Cardiac Disease Detection of Wearable ECG Devices

Xinyan Guan, Yongfan Lai, Jiarui Jin +6

Twelve-lead electrocardiograms (ECGs) are the clinical gold standard for cardiac diagnosis, providing comprehensive spatial coverage of the heart necessary to detect conditions suc…

eess.SP2025

Opportunistic Screening of Wolff-Parkinson-White Syndrome using Single-Lead AI-ECG Mobile System: A Real-World Study of over 3.5 million ECG Recordings in China

Shun Huang, Deyun Zhang, Sumei Fan +9

Wolff-Parkinson-White (WPW) syndrome, a congenital cardiac conduction abnormality with low prevalence, carries a significant risk of sudden cardiac death. Early identification rema…

eess.SP20251 cited

Self-Alignment Learning to Improve Myocardial Infarction Detection from Single-Lead ECG

Jiarui Jin, Xiaocheng Fang, Haoyu Wang +5

Myocardial infarction is a critical manifestation of coronary artery disease, yet detecting it from single-lead electrocardiogram (ECG) remains challenging due to limited spatial i…

cs.LG2025

PPGFlowECG: Latent Rectified Flow with Cross-Modal Encoding for PPG-Guided ECG Generation and Cardiovascular Disease Detection

Xiaocheng Fang, Jiarui Jin, Haoyu Wang +8

Electrocardiography (ECG) is the clinical gold standard for cardiovascular disease (CVD) assessment, yet continuous monitoring is constrained by the need for dedicated hardware and…

cs.LG20251 cited

Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model

Jiarui Jin, Haoyu Wang, Hongyan Li +3

Electrocardiogram (ECG) is essential for the clinical diagnosis of arrhythmias and other heart diseases, but deep learning methods based on ECG often face limitations due to the ne…