1 citations · 2 across the 5 of their papers we have counts for
7 papers
ECGomics: An Open Platform for AI-ECG Digital Biomarker Discovery
Deyun Zhang, Jun Li, Shijia Geng +5
Background: Conventional electrocardiogram (ECG) analysis faces a persistent dichotomy: expert-driven features ensure interpretability but lack sensitivity to latent patterns, whil…
AnyECG: Evolved ECG Foundation Model for Holistic Health Profiling
Jun Li, Hongling Zhu, Yujie Xiao +8
Background: Artificial intelligence enabled electrocardiography (AI-ECG) has demonstrated the ability to detect diverse pathologies, but most existing models focus on single diseas…
AnyECG-Lab: An Exploration Study of Fine-tuning an ECG Foundation Model to Estimate Laboratory Values from Single-Lead ECG Signals
Yujie Xiao, Gongzhen Tang, Wenhui Liu +6
Timely access to laboratory values is critical for clinical decision-making, yet current approaches rely on invasive venous sampling and are intrinsically delayed. Electrocardiogra…
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…
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…
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…