| The effectiveness of image augmentation in deep learning networks for detecting COVID-19: A geometric transformation perspective M Elgendi, MU Nasir, Q Tang, D Smith, JP Grenier, C Batte, B Spieler, ... Frontiers in Medicine 8, 629134, 2021 | 108 | 2021 |
| An automatic diagnosis of arrhythmias using a combination of CNN and LSTM technology Z Zheng, Z Chen, F Hu, J Zhu, Q Tang, Y Liang Electronics 9 (1), 121, 2020 | 84 | 2020 |
| Deep learning algorithm classifies heartbeat events based on electrocardiogram signals Y Liang, S Yin, Q Tang, Z Zheng, M Elgendi, Z Chen Frontiers in Physiology 11, 569050, 2020 | 49 | 2020 |
| Synthetic photoplethysmogram generation using two Gaussian functions Q Tang, Z Chen, R Ward, M Elgendi Scientific Reports 10 (1), 13883, 2020 | 49 | 2020 |
| The performance of deep neural networks in differentiating chest X-rays of COVID-19 patients from other bacterial and viral pneumonias M Elgendi, MU Nasir, Q Tang, RR Fletcher, N Howard, C Menon, R Ward, ... Frontiers in medicine 7, 550, 2020 | 46 | 2020 |
| PPGSynth: An innovative toolbox for synthesizing regular and irregular photoplethysmography waveforms Q Tang, Z Chen, J Allen, A Alian, C Menon, R Ward, M Elgendi Frontiers in Medicine 7, 597774, 2020 | 32 | 2020 |
| Robust reconstruction of electrocardiogram using photoplethysmography: A subject-based Model Q Tang, Z Chen, Y Guo, Y Liang, R Ward, C Menon, M Elgendi Frontiers in Physiology 13, 859763, 2022 | 22 | 2022 |
| PPG2ECGps: An end-to-end subject-specific deep neural network model for electrocardiogram reconstruction from photoplethysmography signals without pulse arrival time adjustments Q Tang, Z Chen, R Ward, C Menon, M Elgendi Bioengineering 10 (6), 630, 2023 | 12 | 2023 |
| Subject-based model for reconstructing arterial blood pressure from Photoplethysmogram Q Tang, Z Chen, R Ward, C Menon, M Elgendi Bioengineering 9 (8), 402, 2022 | 9 | 2022 |
| The effectiveness of image augmentation in deep learning networks for detecting COVID-19: A geometric transformation perspective, Frontiers in Medicine 8. Front. Med.(Lausanne … M Elgendi, MU Nasir, Q Tang, D Smith, JP Grenier, C Batte, B Spieler, ... doi. org/10.3389/fmed, 2021 | 5 | 2021 |
| Improved U-Net Model to Estimate Cardiac Output Based on Photoplethysmography and Arterial Pressure Waveform X Xu, Q Tang, Z Chen Sensors 23 (22), 9057, 2023 | 4 | 2023 |
| Ppgtempstitch: A matlab toolbox for augmenting annotated photoplethsmogram signals Q Tang, Z Chen, C Menon, R Ward, M Elgendi Sensors 21 (12), 4007, 2021 | 3 | 2021 |
| Res-BiANet: A Hybrid Deep Learning Model for Arrhythmia Detection Based on PPG Signal Y Wu, Q Tang, W Zhan, S Li, Z Chen Electronics 13 (3), 665, 2024 | 2 | 2024 |
| UNet-BiLSTM: A Deep Learning Method for Reconstructing Electrocardiography from Photoplethysmography Y Guo, Q Tang, Z Chen, S Li Electronics 13 (10), 1869, 2024 | 1 | 2024 |
| Subject-Independent Model for Reconstructing Electrocardiography Signals from Photoplethysmography Signals Y Guo, S Li, Z Chen, Q Tang Applied Sciences 14 (13), 5773, 2024 | | 2024 |
| Reconstruction of Missing Electrocardiography Signals from Photoplethysmography Data Using Deep Neural Network Y Guo, Q Tang, S Li, Z Chen Bioengineering 11 (4), 365, 2024 | | 2024 |
Mohamed ElgendiProfessor at Khalifa University, former Deputy Director and Lecturer at ETH ZurichEmail verificata su ku.ac.ae