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Qunfeng Tang

Showing results (1-10 of 28) with videos related to

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Sensors (Basel, Switzerland)|November 25, 2023
Improved U-Net Model to Estimate Cardiac Output Based on Photoplethysmography and Arterial Pressure WaveformXichen Xu, Qunfeng Tang, Zhencheng Chen
Bioengineering (Basel, Switzerland)|April 27, 2024
Reconstruction of Missing Electrocardiography Signals from Photoplethysmography Data Using Deep Neural NetworkYanke Guo, Qunfeng Tang, Shiyong Li, et al.
Scientific Reports|August 19, 2020
Synthetic photoplethysmogram generation using two Gaussian functionsQunfeng Tang, Zhencheng Chen, Rabab Ward, et al.
Sensors (Basel, Switzerland)|July 2, 2021
PPGTempStitch: A MATLAB Toolbox for Augmenting Annotated Photoplethsmogram SignalsQunfeng Tang, Zhencheng Chen, Carlo Menon, et al.
Bioengineering (Basel, Switzerland)|August 25, 2022
Subject-Based Model for Reconstructing Arterial Blood Pressure from PhotoplethysmogramQunfeng Tang, Zhencheng Chen, Rabab Ward, et al.
Magnetic Resonance Imaging|August 20, 2019
Correlation of apparent diffusion coefficient and intravoxel incoherent motion imaging parameters with Ki-67 expression in extrahepatic cholangiocarcinomaXingyu Cui, Hongwei Chen, Song Cai, et al.
Bioengineering (Basel, Switzerland)|June 28, 2023
PPG2ECGps: An End-to-End Subject-Specific Deep Neural Network Model for Electrocardiogram Reconstruction from Photoplethysmography Signals without Pulse Arrival Time AdjustmentsQunfeng Tang, Zhencheng Chen, Rabab Ward, et al.
Computer Methods in Biomechanics and Biomedical Engineering|May 25, 2026
A U-Net-based multimodal deep learning model for high-precision blood glucose prediction using non-invasive physiological dataRuting Wang, Li-Ang Gao, Yuhao Xu, et al.
Scientific Reports|December 5, 2024
Robust modelling of arterial blood pressure reconstruction from photoplethysmographyJiating Pan, Lishi Liang, Yongbo Liang, et al.
Frontiers in Physiology|October 29, 2020
Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram SignalsYongbo Liang, Shimin Yin, Qunfeng Tang, et al.
Pageof 3

Showing results (1-10 of 28) with videos related to

Sort By:
Pageof 3
Sensors (Basel, Switzerland)|November 25, 2023
Improved U-Net Model to Estimate Cardiac Output Based on Photoplethysmography and Arterial Pressure WaveformXichen Xu, Qunfeng Tang, Zhencheng Chen
Bioengineering (Basel, Switzerland)|April 27, 2024
Reconstruction of Missing Electrocardiography Signals from Photoplethysmography Data Using Deep Neural NetworkYanke Guo, Qunfeng Tang, Shiyong Li, et al.
Scientific Reports|August 19, 2020
Synthetic photoplethysmogram generation using two Gaussian functionsQunfeng Tang, Zhencheng Chen, Rabab Ward, et al.
Sensors (Basel, Switzerland)|July 2, 2021
PPGTempStitch: A MATLAB Toolbox for Augmenting Annotated Photoplethsmogram SignalsQunfeng Tang, Zhencheng Chen, Carlo Menon, et al.
Bioengineering (Basel, Switzerland)|August 25, 2022
Subject-Based Model for Reconstructing Arterial Blood Pressure from PhotoplethysmogramQunfeng Tang, Zhencheng Chen, Rabab Ward, et al.
Magnetic Resonance Imaging|August 20, 2019
Correlation of apparent diffusion coefficient and intravoxel incoherent motion imaging parameters with Ki-67 expression in extrahepatic cholangiocarcinomaXingyu Cui, Hongwei Chen, Song Cai, et al.
Bioengineering (Basel, Switzerland)|June 28, 2023
PPG2ECGps: An End-to-End Subject-Specific Deep Neural Network Model for Electrocardiogram Reconstruction from Photoplethysmography Signals without Pulse Arrival Time AdjustmentsQunfeng Tang, Zhencheng Chen, Rabab Ward, et al.
Computer Methods in Biomechanics and Biomedical Engineering|May 25, 2026
A U-Net-based multimodal deep learning model for high-precision blood glucose prediction using non-invasive physiological dataRuting Wang, Li-Ang Gao, Yuhao Xu, et al.
Scientific Reports|December 5, 2024
Robust modelling of arterial blood pressure reconstruction from photoplethysmographyJiating Pan, Lishi Liang, Yongbo Liang, et al.
Frontiers in Physiology|October 29, 2020
Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram SignalsYongbo Liang, Shimin Yin, Qunfeng Tang, et al.
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