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Xujian Feng

Showing results (1-10 of 7) with videos related to

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet TransformZiqian Wu, Xujian Feng, Cuiwei Yang
Frontiers in Physiology|November 25, 2022
A 3D-CNN with temporal-attention block to predict the recurrence of atrial fibrillation based on body-surface potential mapping signalsGaoyan Zhong, Xujian Feng, Han Yuan, et al.
Journal of Interventional Cardiac Electrophysiology : an International Journal of Arrhythmias and Pacing|April 25, 2023
A "two-step classification" machine learning method for non-invasive localization of premature ventricular contraction origins based on 12-lead ECGYiwen Wang, Xujian Feng, Gaoyan Zhong, et al.
Pacing and Clinical Electrophysiology : PACE|October 21, 2024
Machine Learning for Localization of Premature Ventricular Contraction Origins: A ReviewRui Yang, Yiwen Wang, Yanan Wang, et al.
Journal of Cardiovascular Electrophysiology|May 23, 2025
A Deep Learning-Based Multimodal Fusion Model for Recurrence Prediction in Persistent Atrial Fibrillation PatientsLi Chen, Xujian Feng, Haonan Chen, et al.
Phenomics (Cham, Switzerland)|March 10, 2025
Risk Analysis of Atrial Fibrillation Based on ECG Phenotypes: The RAF-ECP Study ProtocolAiguo Wang, Jiacheng He, Xujian Feng, et al.
Computer Methods and Programs in Biomedicine|February 24, 2024
Intelligent assessment of atrial fibrillation gradation based on sinus rhythm electrocardiogram and baseline informationBiqi Tang, Sen Liu, Xujian Feng, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet TransformZiqian Wu, Xujian Feng, Cuiwei Yang
Frontiers in Physiology|November 25, 2022
A 3D-CNN with temporal-attention block to predict the recurrence of atrial fibrillation based on body-surface potential mapping signalsGaoyan Zhong, Xujian Feng, Han Yuan, et al.
Journal of Interventional Cardiac Electrophysiology : an International Journal of Arrhythmias and Pacing|April 25, 2023
A "two-step classification" machine learning method for non-invasive localization of premature ventricular contraction origins based on 12-lead ECGYiwen Wang, Xujian Feng, Gaoyan Zhong, et al.
Pacing and Clinical Electrophysiology : PACE|October 21, 2024
Machine Learning for Localization of Premature Ventricular Contraction Origins: A ReviewRui Yang, Yiwen Wang, Yanan Wang, et al.
Journal of Cardiovascular Electrophysiology|May 23, 2025
A Deep Learning-Based Multimodal Fusion Model for Recurrence Prediction in Persistent Atrial Fibrillation PatientsLi Chen, Xujian Feng, Haonan Chen, et al.
Phenomics (Cham, Switzerland)|March 10, 2025
Risk Analysis of Atrial Fibrillation Based on ECG Phenotypes: The RAF-ECP Study ProtocolAiguo Wang, Jiacheng He, Xujian Feng, et al.
Computer Methods and Programs in Biomedicine|February 24, 2024
Intelligent assessment of atrial fibrillation gradation based on sinus rhythm electrocardiogram and baseline informationBiqi Tang, Sen Liu, Xujian Feng, et al.
Pageof 1