22 citations · 28 across the 20 of their papers we have counts for
22 papers
EchoBridge: Long-Tail-Aware ECG-Echocardiography Text Alignment for Echocardiography-Derived Cardiac Findings
Xiaocheng Fang, Jieyi Cai, Guangkun Nie +9
Standardized echocardiography conclusions provide meaningful supervision for learning ECG representations of echocardiography-derived cardiac findings. Global ECG--text alignment m…
ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment
Xiaocheng Fang, Haoyu Wang, Jieyi Cai +14
Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly those digitized from ECG imag…
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…
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…
Aortic Valve Disease Screening from PPG via Physiology-Guided Self-Supervised Learning
Jiaze Wang, Qinghao Zhao, Zizheng Chen +4
Aortic valve disease (AVD) represents a major public health burden, while its diagnosis relies on echocardiography, which is limited by cost and specialist expertise, restricting s…
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…
Fine-tuning an ECG Foundation Model to Predict Coronary CT Angiography Outcomes
Yujie Xiao, Qinghao Zhao, Gongzheng Tang +12
Coronary artery disease (CAD) remains a major global public health burden, yet scalable pre-imaging risk stratification tools are limited. In this multicenter study, we developed a…
Artificial Intelligence-Enabled Spirometry for Early Detection of Right Heart Failure
Bin Liu, Qinghao Zhao, Yuxi Zhou +5
Right heart failure (RHF) is a disease characterized by abnormalities in the structure or function of the right ventricle (RV), which is associated with high morbidity and mortalit…
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…
UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Haoming Wang, Haoyang Zou, Huatong Song +109
The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have sh…
Masked Training for Robust Arrhythmia Detection from Digitalized Multiple Layout ECG Images
Shanwei Zhang, Deyun Zhang, Yirao Tao +9
Background: Electrocardiograms are indispensable for diagnosing cardiovascular diseases, yet in many settings they exist only as paper printouts stored in multiple recording layout…
ECGTwin: Personalized ECG Generation Using Controllable Diffusion Model
Yongfan Lai, Bo Liu, Xinyan Guan +3
Personalized electrocardiogram (ECG) generation is to simulate a patient's ECG digital twins tailored to specific conditions. It has the potential to transform traditional healthca…
MEETI: A Multimodal ECG Dataset from MIMIC-IV-ECG with Signals, Images, Features and Interpretations
Deyun Zhang, Xiang Lan, Shijia Geng +4
Electrocardiogram (ECG) plays a foundational role in modern cardiovascular care, enabling non-invasive diagnosis of arrhythmias, myocardial ischemia, and conduction disorders. Whil…
GEM: Empowering MLLM for Grounded ECG Understanding with Time Series and Images
Xiang Lan, Feng Wu, Kai He +3
While recent multimodal large language models (MLLMs) have advanced automated ECG interpretation, they still face two key limitations: (1) insufficient multimodal synergy between t…
On-device Computation of Single-lead ECG Parameters for Real-time Remote Cardiac Health Assessment: A Real-world Validation Study
Sumei Fan, Deyun Zhang, Yue Wang +9
Accurate, continuous out-of-hospital electrocardiogram (ECG) parameter measurement is vital for real-time cardiac health monitoring and telemedicine. On-device computation of singl…
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…
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…
Deep Learning for Detecting and Early Predicting Chronic Obstructive Pulmonary Disease from Spirogram Time Series
Shuhao Mei, Xin Li, Yuxi Zhou +9
Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent fe…
A Deep Learning Method for Beat-Level Risk Analysis and Interpretation of Atrial Fibrillation Patients during Sinus Rhythm
Jun Lei, Yuxi Zhou, Xue Tian +5
Atrial Fibrillation (AF) is a common cardiac arrhythmia. Many AF patients experience complications such as stroke and other cardiovascular issues. Early detection of AF is crucial.…
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…
Artificial Intelligence System for Detection and Screening of Cardiac Abnormalities using Electrocardiogram Images
Deyun Zhang, Shijia Geng, Yang Zhou +28
The artificial intelligence (AI) system has achieved expert-level performance in electrocardiogram (ECG) signal analysis. However, in underdeveloped countries or regions where the…