Zequn Liu
Zequn Liu
Verified email at pku.edu.cn
Title
Cited by
Cited by
Year
Deep learning on automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy
AJ Hung, J Chen, S Ghodoussipour, PJ Oh, Z Liu, J Nguyen, ...
BJU international 124 (3), 487, 2019
442019
Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks
Y Song, Z Liu, W Bi, R Yan, M Zhang
arXiv preprint arXiv:1910.14326, 2019
13*2019
Early Prediction of Sepsis From Clinical Data via Heterogeneous Event Aggregation
L Liu, H Wu, Z Wang, Z Liu, M Zhang
2019 Computing in Cardiology (CinC), Page 1-Page 4, 2019
62019
Multi-task learning via adaptation to similar tasks for mortality prediction of diverse rare diseases
L Liu, Z Liu, H Wu, Z Wang, J Shen, Y Song, M Zhang
AMIA Annual Symposium Proceedings 2020, 763, 2020
52020
When does maml work the best? an empirical study on model-agnostic meta-learning in nlp applications
Z Liu, R Zhang, Y Song, M Zhang
arXiv preprint arXiv:2005.11700, 2020
22020
PD27-07 DEEP LEARNING MODEL TO PREDICT TIME TO URINARY CONTINENCE RECOVERY AFTER ROBOT-ASSISTED RADICAL PROSTATECTOMY USING AUTOMATED PERFORMANCE METRICS AND CLINICAL DATA
A Hung*, J Chen, Z Liu, J Nguyen, P Oh, D Stewart, D Remulla, T Chu, ...
The Journal of Urology 201 (Supplement 4), e483-e483, 2019
12019
Graphine: A Dataset for Graph-aware Terminology Definition Generation
Z Liu, S Wang, Y Gu, R Zhang, M Zhang, S Wang
arXiv preprint arXiv:2109.04018, 2021
2021
MP60-14 COMPARING DEEP LEARNING, MACHINE LEARNING, AND CONVENTIONAL REGRESSION AS PREDICTIVE MODELS OF TIME TO URINARY CONTINENCE AFTER ROBOT-ASSISTED RADICAL PROSTATECTOMY
A Hung*, J Chen, Z Liu, J Nguyen, S Purushotham, Y Liu
The Journal of Urology 201 (Supplement 4), e874-e874, 2019
2019
Deep learning model to predict urinary continence after robot-assisted radical prostatectomy
A Hung, J Chen, ZQ Liu, J Nguyen, S Purushotham, Y Liu
European Urology Supplements 18 (1), e851, 2019
2019
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