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Shaowen Qin
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- affiliation: Flinders University, Bedford Park, South Australia, Australia
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2020 – today
- 2024
- [j5]Jin Ye
, Shaowen Qin
Adaptive Bitrate Algorithms via Deep Reinforcement Learning With Digital Twins Assisted Trajectory. IEEE Trans. Netw. Sci. Eng. 11(4): 3522-3535 (2024) - [c22]Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim, Jiang Bian, Antonio Jimeno-Yepes:
Fine-grained Patient Similarity Measuring using Contrastive Graph Similarity Networks. ICHI 2024: 1-10 - [c21]Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim, Antonio Jimeno-Yepes, Jun Shen, Jiang Bian:
Hypergraph Convolutional Networks for Fine-Grained lCU Patient Similarity Analysis and Risk Prediction. ICHI 2024: 123-128 - [c20]Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Jiang Bian:
Multi-Task Deep Neural Networks for Irregularly Sampled Multivariate Clinical Time Series. ICHI 2024: 135-140 - [c19]Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim:
A Multi-Graph Fusion Framework for Patient Representation Learning. ICHI 2024: 222-227 - 2023
- [c18]David Ben-Tovim, Mariusz Bajger
A Novel Application of a Mutual Information Measure for Analysing Temporal Changes in Healthcare Network Graphs. ADMA (3) 2023: 92-102 - [c17]Yuxi Liu, Zhenhao Zhang, Shaowen Qin:
NeuralHMM: A Deep Markov Network for Health Risk Prediction using Electronic Health Records. IJCNN 2023: 1-8 - [c16]Yuxi Liu, Zhenhao Zhang, Shaowen Qin:
Deep Imputation-Prediction Networks for Health Risk Prediction using Electronic Health Records. IJCNN 2023: 1-9 - [c15]Yuxi Liu, Zhenhao Zhang, Campbell Thompson, Richard Leibbrandt
Stacked Attention-based Networks for Accurate and Interpretable Health Risk Prediction. IJCNN 2023: 1-8 - [c14]Shaowen Qin, Jin Ye, Xin Tang, Xiaohuan Li:
Stackelberg Game-Base Incentive Scheme for Federated Learning in Artificial Intelligence of Things. iThings/GreenCom/CPSCom/SmartData/Cybermatics 2023: 159-165 - [c13]Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim, Antonio Jimeno-Yepes:
Contrastive Learning-Based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling Using EHRs. ECML/PKDD (6) 2023: 428-443 - [i4]Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim, Antonio Jimeno-Yepes:
Contrastive Learning-based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling using EHRs. CoRR abs/2308.09896 (2023) - [i3]Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim, Antonio Jimeno-Yepes, Jun Shen
Hypergraph Convolutional Networks for Fine-grained ICU Patient Similarity Analysis and Risk Prediction. CoRR abs/2308.12575 (2023) - 2022
- [c12]Yuxi Liu, Shaowen Qin, Zhenhao Zhang, Wei Shao
Compound Density Networks for Risk Prediction using Electronic Health Records. BIBM 2022: 1078-1085 - [c11]Yuxi Liu, Shaowen Qin, Antonio Jimeno-Yepes, Wei Shao
Integrated Convolutional and Recurrent Neural Networks for Health Risk Prediction using Patient Journey Data with Many Missing Values. BIBM 2022: 1658-1663 - [c10]Yuxi Liu, Shaowen Qin:
Hospital Readmission Prediction via Personalized Feature Learning and Embedding: A Novel Deep Learning Framework. IEA/AIE 2022: 89-100 - [c9]Yuxi Liu, Shaowen Qin, Zhenhao Zhang:
Epidemic Modeling of the Spatiotemporal Spread of COVID-19 over an Intercity Population Mobility Network. IEA/AIE 2022: 147-159 - [i2]Yuxi Liu, Zhenhao Zhang, Shaowen Qin:
Compound Density Networks for Risk Prediction using Electronic Health Records. CoRR abs/2208.01320 (2022) - [i1]Yuxi Liu, Shaowen Qin, Antonio Jimeno-Yepes, Wei Shao
Integrated Convolutional and Recurrent Neural Networks for Health Risk Prediction using Patient Journey Data with Many Missing Values. CoRR abs/2211.06045 (2022) - 2021
- [c8]David Ben-Tovim, Mariusz Bajger
Network Graph Analysis of Hospital and Health Services Functional Structures. ADMA 2021: 33-44 - [c7]Yuxi Liu
An Interpretable Machine Learning Approach for Predicting Hospital Length of Stay and Readmission. ADMA 2021: 73-85
2010 – 2019
- 2019
- [c6]Shaowen Qin
Using a Virtual Hospital for Piloting Patient Flow Decongestion Interventions. ADMA 2019: 605-616 - [e1]Jianxin Li, Sen Wang
Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Dalian, China, November 21-23, 2019, Proceedings. Lecture Notes in Computer Science 11888, Springer 2019, ISBN 978-3-030-35230-1 [contents] - 2018
- [c5]Shaowen Qin, Dale Ward:
Forecasting Hospital Daily Occupancy Using Patient Journey Data - A Heuristic Approach. ADMA 2018: 150-159 - 2016
- [j4]David Ben-Tovim, Jerzy A. Filar
Hospital Event Simulation Model: Arrivals to Discharge-Design, development and application. Simul. Model. Pract. Theory 68: 80-94 (2016) - 2010
- [j3]Hussain Alfaraj, Shaowen Qin
Deriving Software Acquisition Process from Maturity Models - An Experience Report. J. Softw. Eng. Appl. 3(3): 280-286 (2010)
2000 – 2009
- 2009
- [j2]Kevin Chiew, Shaowen Qin
Scheduling and Routing of AMOs in an Intelligent Transport System. IEEE Trans. Intell. Transp. Syst. 10(3): 547-552 (2009) - [c4]Shaowen Qin, Bei-Bei Yin, Kai-Yuan Cai:
Mining Components with Software Execution Data. Software Engineering Research and Practice 2009: 643-649 - 2008
- [c3]Trent Kroeger, Fengdi Shu, Shaowen Qin:
A Defect Typology to Support Software Process Verification and Validation. Software Engineering Research and Practice 2008: 245-250 - 2007
- [j1]Shaowen Qin
Managing process change in software organizations: Experience and reflection. Softw. Process. Improv. Pract. 12(5): 429-435 (2007) - [c2]Xuemei Zhao, Karl Sammut
Split Private and Shared L2 Cache Architecture for Snooping-based CMP. ACIS-ICIS 2007: 900-905 - 2006
- [c1]Shaowen Qin
Implementing Process Change in a Software Organization - An Experience Based Study. SPW/ProSim 2006: 342-347
Coauthor Index
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last updated on 2024-10-21 20:26 CEST by the dblp team
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