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Shenda Hong
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Year
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
2032020
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
1332017
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
552019
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
512019
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), 1-16, 2021
332021
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
272020
Diffusion models: A comprehensive survey of methods and applications
L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao, Y Shao, W Zhang, B Cui, ...
arXiv preprint arXiv:2209.00796, 2022
252022
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
232021
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
212020
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, 2022
20*2022
Classifying vaguely labeled data based on evidential fusion
M Song, C Sun, D Cai, S Hong, H Li
Information Sciences 583, 159-173, 2022
192022
Artificial-intelligence-enhanced mobile system for cardiovascular health management
Z Fu, S Hong, R Zhang, S Du
Sensors 21 (3), 773, 2021
192021
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
International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2019
182019
Event2vec: Learning representations of events on temporal sequences
S Hong, M Wu, H Li, Z Wu
Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint …, 2017
152017
CardioID: Learning to identification from electrocardiogram data
S Hong, C Wang, Z Fu
Neurocomputing 412, 11-18, 2020
102020
Cardiolearn: a cloud deep learning service for cardiac disease detection from electrocardiogram
S Hong, Z Fu, R Zhou, J Yu, Y Li, K Wang, G Cheng
Companion Proceedings of the Web Conference 2020, 148-152, 2020
102020
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
102018
Deep active learning for interictal ictal injury continuum EEG patterns
W Ge, J Jing, S An, A Herlopian, M Ng, AF Struck, B Appavu, EL Johnson, ...
Journal of neuroscience methods 351, 108966, 2021
82021
RDPD: rich data helps poor data via imitation
S Hong, C Xiao, TN Hoang, T Ma, H Li, J Sun
International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2019
72019
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
62022
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