1 citations · 1 across the 11 of their papers we have counts for
13 papers
Wearable Single-Lead ECG Detects Fine-Grained Structural Heart Disease Through Echo-Report Supervision
Chenyang He, Qinghao Zhao, Shun Huang +9
Structural heart disease (SHD) is a primary driver of heart failure and cardiovascular mortality, yet early detection remains constrained by the limited accessibility of echocardio…
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…
Artificial intelligence-enabled single-lead ECG for non-invasive hyperkalemia detection: development, multicenter validation, and proof-of-concept deployment
Gongzheng Tang, Qinghao Zhao, Guangkun Nie +10
Hyperkalemia is a life-threatening electrolyte disorder that is common in patients with chronic kidney disease and heart failure, yet frequent monitoring remains difficult outside…
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…
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…
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…
Combining ECG Foundation Model and XGBoost to Predict In-Hospital Malignant Ventricular Arrhythmias in AMI Patients
Shun Huang, Wenlu Xing, Shijia Geng +5
Malignant ventricular arrhythmias (VT/VF) following acute myocardial infarction (AMI) are a major cause of in-hospital death, yet early identification remains a clinical challenge.…
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…
KidneyTalk-open: No-code Deployment of a Private Large Language Model with Medical Documentation-Enhanced Knowledge Database for Kidney Disease
Yongchao Long, Chao Yang, Gongzheng Tang +5
Privacy-preserving medical decision support for kidney disease requires localized deployment of large language models (LLMs) while maintaining clinical reasoning capabilities. Curr…
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…
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
Guangkun Nie, Gongzheng Tang, Shenda Hong
Imbalanced data distributions are prevalent in real-world scenarios, posing significant challenges in both imbalanced classification and imbalanced regression tasks. They often cau…
Deep Imbalanced Regression to Estimate Vascular Age from PPG Data: a Novel Digital Biomarker for Cardiovascular Health
Guangkun Nie, Qinghao Zhao, Gongzheng Tang +2
Photoplethysmography (PPG) is emerging as a crucial tool for monitoring human hemodynamics, with recent studies highlighting its potential in assessing vascular aging through deep…
A Scoping Review of Deep Learning Methods for Photoplethysmography Data
Guangkun Nie, Jiabao Zhu, Gongzheng Tang +4
Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad deployment in both clinical monitoring…