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Zhoujian Sun

Showing results (1-10 of 12) with videos related to

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Physical Review Letters|February 6, 2025
Defect Production across Higher-Order Phase Transitions beyond Kibble-Zurek ScalingMenghua Deng, Zhoujian Sun, Fuxiang Li
BMC Medical Informatics and Decision Making|January 11, 2019
Utilizing dynamic treatment information for MACE prediction of acute coronary syndromeHuilong Duan, Zhoujian Sun, Wei Dong, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Learning Representations from Medical Text for Effective Diagnoses and Knowledge DiscoveryZhoujian Sun, Hanrui Shi, Zhengxing Huang, et al.
Journal of Biomedical Informatics|November 3, 2021
On learning disentangled representations for individual treatment effect estimationJiebin Chu, Zhoujian Sun, Wei Dong, et al.
IEEE Journal of Biomedical and Health Informatics|July 30, 2021
Towards Predictive Analysis on Disease Progression: A Variational Hawkes Process ModelZhaohong Sun, Zhoujian Sun, Wei Dong, et al.
Iscience|June 13, 2024
Linguistic feedback supports rapid adaptation to acoustically degraded speechWenhui Sun, Jiajie Zou, Tianyi Zhu, et al.
IEEE Journal of Biomedical and Health Informatics|December 28, 2019
On Clinical Event Prediction in Patient Treatment Trajectory Using Longitudinal Electronic Health RecordsHuilong Duan, Zhoujian Sun, Wei Dong, et al.
Physical Review Letters|November 7, 2025
Exchange Surface Spin Waves in Type-A van der Waals AntiferromagnetsZhoujian Sun, Fuxiang Li, Gerrit E W Bauer, et al.
Frontiers in Cardiovascular Medicine|April 25, 2022
Comparing Machine Learning Models and Statistical Models for Predicting Heart Failure Events: A Systematic Review and Meta-AnalysisZhoujian Sun, Wei Dong, Hanrui Shi, et al.
JMIR Medical Informatics|October 14, 2022
Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning ApproachCaogen Hong, Zhoujian Sun, Yuzhe Hao, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Physical Review Letters|February 6, 2025
Defect Production across Higher-Order Phase Transitions beyond Kibble-Zurek ScalingMenghua Deng, Zhoujian Sun, Fuxiang Li
BMC Medical Informatics and Decision Making|January 11, 2019
Utilizing dynamic treatment information for MACE prediction of acute coronary syndromeHuilong Duan, Zhoujian Sun, Wei Dong, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Learning Representations from Medical Text for Effective Diagnoses and Knowledge DiscoveryZhoujian Sun, Hanrui Shi, Zhengxing Huang, et al.
Journal of Biomedical Informatics|November 3, 2021
On learning disentangled representations for individual treatment effect estimationJiebin Chu, Zhoujian Sun, Wei Dong, et al.
IEEE Journal of Biomedical and Health Informatics|July 30, 2021
Towards Predictive Analysis on Disease Progression: A Variational Hawkes Process ModelZhaohong Sun, Zhoujian Sun, Wei Dong, et al.
Iscience|June 13, 2024
Linguistic feedback supports rapid adaptation to acoustically degraded speechWenhui Sun, Jiajie Zou, Tianyi Zhu, et al.
IEEE Journal of Biomedical and Health Informatics|December 28, 2019
On Clinical Event Prediction in Patient Treatment Trajectory Using Longitudinal Electronic Health RecordsHuilong Duan, Zhoujian Sun, Wei Dong, et al.
Physical Review Letters|November 7, 2025
Exchange Surface Spin Waves in Type-A van der Waals AntiferromagnetsZhoujian Sun, Fuxiang Li, Gerrit E W Bauer, et al.
Frontiers in Cardiovascular Medicine|April 25, 2022
Comparing Machine Learning Models and Statistical Models for Predicting Heart Failure Events: A Systematic Review and Meta-AnalysisZhoujian Sun, Wei Dong, Hanrui Shi, et al.
JMIR Medical Informatics|October 14, 2022
Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning ApproachCaogen Hong, Zhoujian Sun, Yuzhe Hao, et al.
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