Diffusion models: A comprehensive survey of methods and applications L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao, W Zhang, B Cui, ... ACM Computing Surveys 56 (4), 1-39, 2023 | 859 | 2023 |
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, 103801, 2020 | 391 | 2020 |
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 | 172 | 2017 |
Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion L Yang, S Hong International conference on machine learning, 25038-25054, 2022 | 91 | 2022 |
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 |
MINA: multilevel knowledge-guided attention for modeling electrocardiography signals S Hong, C Xiao, T Ma, H Li, J Sun International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2019 | 77 | 2019 |
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units S Hong, Y Xu, A Khare, S Priambada, K Maher, A Aljiffry, J Sun, ... Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 74 | 2020 |
A systematic review of echo state networks from design to application C Sun, M Song, D Cai, B Zhang, S Hong, H Li IEEE Transactions on Artificial Intelligence 5 (1), 23-37, 2022 | 69* | 2022 |
Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning C Sun, S Hong, M Song, H Li, Z Wang BMC Medical Informatics and Decision Making 21, 1-16, 2021 | 58 | 2021 |
Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning G Spadon, S Hong, B Brandoli, S Matwin, JF Rodrigues-Jr, J Sun IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 55 | 2021 |
A review of deep learning methods for irregularly sampled medical time series data C Sun, S Hong, M Song, H Li arXiv preprint arXiv:2010.12493, 2020 | 55 | 2020 |
Artificial-intelligence-enhanced mobile system for cardiovascular health management Z Fu, S Hong, R Zhang, S Du Sensors 21 (3), 773, 2021 | 44 | 2021 |
Classifying vaguely labeled data based on evidential fusion M Song, C Sun, D Cai, S Hong, H Li Information Sciences 583, 159-173, 2022 | 42 | 2022 |
TEST: Text prototype aligned embedding to activate LLM's ability for time series C Sun, Y Li, H Li, S Hong International Conference on Learning Representations 2024, 2024 | 38 | 2024 |
Intra-inter subject self-supervised learning for multivariate cardiac signals X Lan, D Ng, S Hong, M Feng Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4532-4540, 2022 | 37 | 2022 |
Predicting neurological outcome in comatose patients after cardiac arrest with multiscale deep neural networks WL Zheng, E Amorim, J Jing, W Ge, S Hong, O Wu, M Ghassemi, JW Lee, ... Resuscitation 169, 86-94, 2021 | 36 | 2021 |
Frozen language model helps ecg zero-shot learning J Li, C Liu, S Cheng, R Arcucci, S Hong Medical Imaging with Deep Learning, 402-415, 2024 | 31 | 2024 |
Diffusion-based scene graph to image generation with masked contrastive pre-training L Yang, Z Huang, Y Song, S Hong, G Li, W Zhang, B Cui, B Ghanem, ... arXiv preprint arXiv:2211.11138, 2022 | 28 | 2022 |
Basiliximab for steroid‐refractory acute graft‐versus‐host disease: a real‐world analysis XD Mo, SD Hong, YL Zhao, EL Jiang, J Chen, Y Xu, ZM Sun, WJ Zhang, ... American Journal of Hematology, 2022 | 28 | 2022 |
A comprehensive model to predict severe acute graft-versus-host disease in acute leukemia patients after haploidentical hematopoietic stem cell transplantation MZ Shen, SD Hong, R Lou, RZ Chen, XH Zhang, LP Xu, Y Wang, CH Yan, ... Experimental hematology & oncology 11 (1), 25, 2022 | 26 | 2022 |