10 citations · 26 across the 8 of their papers we have counts for
9 papers
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…
Self-Supervised Time Series Representation Learning via Cross Reconstruction Transformer
Wenrui Zhang, Ling Yang, Shijia Geng +1
Unsupervised/self-supervised representation learning in time series is critical since labeled samples are usually scarce in real-world scenarios. Existing approaches mainly leverag…
Defending Against Adversarial Attack in ECG Classification with Adversarial Distillation Training
Jiahao Shao, Shijia Geng, Zhaoji Fu +3
In clinics, doctors rely on electrocardiograms (ECGs) to assess severe cardiac disorders. Owing to the development of technology and the increase in health awareness, ECG signals a…
MetaVA: Curriculum Meta-learning and Pre-fine-tuning of Deep Neural Networks for Detecting Ventricular Arrhythmias based on ECGs
Wenrui Zhang, Shijia Geng, Zhaoji Fu +3
Ventricular arrhythmias (VA) are the main causes of sudden cardiac death. Developing machine learning methods for detecting VA based on electrocardiograms (ECGs) can help save peop…
A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification with Rejection from ECG Recordings
Wenrui Zhang, Xinxin Di, Guodong Wei +3
With the development of deep learning-based methods, automated classification of electrocardiograms (ECGs) has recently gained much attention. Although the effectiveness of deep ne…
A Simple Self-Supervised ECG Representation Learning Method via Manipulated Temporal-Spatial Reverse Detection
Wenrui Zhang, Shijia Geng, Shenda Hong
Learning representations from electrocardiogram (ECG) signals can serve as a fundamental step for different machine learning-based ECG tasks. In order to extract general ECG repres…
Transforming Musical Signals through a Genre Classifying Convolutional Neural Network
S. Geng, G. Ren, M. Ogihara
Convolutional neural networks (CNNs) have been successfully applied on both discriminative and generative modeling for music-related tasks. For a particular task, the trained CNN c…