| Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review S Hong, Y Zhou, J Shang, C Xiao, J Sun Computers in biology and medicine 122, 103801, 2020 | 375 | 2020 |
| Ernie 3.0: Large-scale knowledge enhanced pre-training for language understanding and generation Y Sun, S Wang, S Feng, S Ding, C Pang, J Shang, J Liu, X Chen, Y Zhao, ... arXiv preprint arXiv:2107.02137, 2021 | 329 | 2021 |
| Pre-training of graph augmented transformers for medication recommendation J Shang, T Ma, C Xiao, J Sun arXiv preprint arXiv:1906.00346, 2019 | 250 | 2019 |
| Gamenet: Graph augmented memory networks for recommending medication combination J Shang, C Xiao, T Ma, H Li, J Sun proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1126-1133, 2019 | 208 | 2019 |
| ENCASE: An ENsemble ClASsifiEr for ECG classification using expert features and deep neural networks S Hong, M Wu, Y Zhou, Q Wang, J Shang, H Li, J Xie 2017 Computing in cardiology (cinc), 1-4, 2017 | 164 | 2017 |
| Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings S Hong, Y Zhou, M Wu, J Shang, Q Wang, H Li, J Xie Physiological measurement 40 (5), 054009, 2019 | 78 | 2019 |
| Ernie 3.0 titan: Exploring larger-scale knowledge enhanced pre-training for language understanding and generation S Wang, Y Sun, Y Xiang, Z Wu, S Ding, W Gong, S Feng, J Shang, Y Zhao, ... arXiv preprint arXiv:2112.12731, 2021 | 55 | 2021 |
| ERNIE-Doc: A retrospective long-document modeling transformer S Ding, J Shang, S Wang, Y Sun, H Tian, H Wu, H Wang arXiv preprint arXiv:2012.15688, 2020 | 52 | 2020 |
| K-margin-based residual-convolution-recurrent neural network for atrial fibrillation detection Y Zhou, S Hong, J Shang, M Wu, Q Wang, H Li, J Xie arXiv preprint arXiv:1908.06857, 2019 | 23 | 2019 |
| Ernie 3.0: Large-scale knowledge enhanced pre-training for language understanding and generation. arXiv Y Sun, S Wang, S Feng, S Ding, C Pang, J Shang, J Liu, X Chen, Y Zhao, ... arXiv preprint arXiv:2107.02137, 2021 | 17 | 2021 |
| Knowledge-shot learning: An interpretable deep model for classifying imbalanced electrocardiography data Y Chou, S Hong, Y Zhou, J Shang, M Song, H Li Neurocomputing 417, 64-73, 2020 | 16 | 2020 |
| Genn: predicting correlated drug-drug interactions with graph energy neural networks T Ma, J Shang, C Xiao, J Sun arXiv preprint arXiv:1910.02107, 2019 | 14 | 2019 |
| Knowledge guided multi-instance multi-label learning via neural networks in medicines prediction J Shang, S Hong, Y Zhou, M Wu, H Li Asian Conference on Machine Learning, 831-846, 2018 | 13 | 2018 |
| Addressing noise and skewness in interpretable health-condition assessment by learning model confidence Y Zhou, S Hong, J Shang, M Wu, Q Wang, H Li, J Xie Sensors 20 (24), 7307, 2020 | 10 | 2020 |
| Personalized vital signs control based on continuous action-space reinforcement learning with supervised experience C Sun, S Hong, M Song, J Shang, H Li Biomedical Signal Processing and Control 69, 102847, 2021 | 9 | 2021 |
| Cgnf: Conditional graph neural fields T Ma, C Xiao, J Shang, J Sun | 5 | 2018 |
| Method and apparatus of training natural language processing model, and method and apparatus of processing natural language D Siyu, P Chao, W Shuohuan, Y Zhao, J Shang, Y Sun, F Shikun, H Tian, ... US Patent App. 17/828,773, 2022 | 3 | 2022 |
| X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications J Shang, S Wang, Y Sun, Y Yu, Y Zhou, L Xiang, G Yang arXiv preprint arXiv:2211.14734, 2022 | 1 | 2022 |
| Method for pre-training language model J Shang, W Shuohuan, D Siyu, Y Zhao, P Chao, Y Sun, H Tian, H Wu, ... US Patent App. 18/179,627, 2023 | | 2023 |
| Method for pre-training model, device, and storage medium J Shang, W Shuohuan, D Siyu, Y Zhao, P Chao, Y Sun US Patent App. 17/889,218, 2023 | | 2023 |
Shenda HongAssistant Professor, Peking UniversityAdresse e-mail validée de pku.edu.cn
