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20242026
most citedDeep Imbalanced Regression to Estimate Vascular Age from PPG Data: a Novel Digital Biomarker for Cardiovascular Health

1 citations · 1 across the 15 of their papers we have counts for

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eess.SP2026

Smartwatch Photoplethysmography-Derived Heart Age via ECG-Guided Cross-Modal Pretraining as a Digital Biomarker of Vascular Aging

Donglin Xie, Xueying Gui, Yutian Zhu +9

Digital biomarkers of cardiovascular aging, often termed heart or vascular age, have been widely studied, but most rely on resting electrocardiography (ECG), imaging, or specialize…

eess.SP2026

Holter-to-Sleep: AI-Enabled Repurposing of Single-Lead ECG for Sleep Phenotyping

Donglin Xie, Qingshuo Zhao, Jingyu Wang +9

Sleep disturbances are tightly linked to cardiovascular risk, yet polysomnography (PSG)-the clinical reference standard-remains resource-intensive and poorly suited for multi-night…

eess.SP2026

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…

eess.SP2025

AnyPPG: An ECG-Guided PPG Foundation Model Trained on Over 100,000 Hours of Recordings for Holistic Health Profiling

Guangkun Nie, Xiaocheng Fang, Gongzheng Tang +5

Photoplethysmography (PPG) is widely used as a non-invasive and accessible modality for continuous health monitoring. However, despite being a peripheral hemodynamic signal intrins…

eess.SP2025

Artificial Intelligence-derived Photoplethysmography Age as a Digital Biomarker for Cardiovascular Health

Guangkun Nie, Qinghao Zhao, Gongzheng Tang +2

Background: Photoplethysmography (PPG), increasingly available through wearable devices, provides a non-invasive means of monitoring human hemodynamics. In this study, we introduce…