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Julie S. Ivy
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- affiliation: North Carolina State University, Department of Industrial and Systems Engineering
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2020 – today
- 2023
- [c25]Yiwei Zhang, Maria E. Mayorga, Julie S. Ivy, Julie L. Swann:
Multi-Criteria Simulation Optimization for COVID-19 Testing In Schools. WSC 2023: 1006-1017 - 2022
- [j16]Erik T. Rosenstrom
, Sareh Meshkinfam
Optimizing the First Response to Sepsis: An Electronic Health Record-Based Markov Decision Process Model. Decis. Anal. 19(4): 265-296 (2022) - [j15]Md Hafizul Islam
Modeling the role of efficiency for the equitable and effective distribution of donated food. OR Spectr. 44(2): 485-534 (2022) - [j14]Breanna P. Swan
The SMART Framework: Selection of Machine Learning Algorithms With ReplicaTions - A Case Study on the Microvascular Complications of Diabetes. IEEE J. Biomed. Health Informatics 26(2): 809-817 (2022) - [c24]Erik T. Rosenstrom
Could Earlier Availability of Boosters and Pediatric Vaccines Have Reduced Impact of COVID-19? WSC 2022: 1-12 - [c23]Danika Dorris, Julie S. Ivy, Julie L. Swann
An Approach to Population Synthesis of Engineering Students for Understanding Dropout Risk. WSC 2022: 677-688 - 2021
- [j13]Ali Jazayeri
Proximity of Cellular and Physiological Response Failures in Sepsis. IEEE J. Biomed. Health Informatics 25(11): 4089-4097 (2021) - [c22]Esha Sharma, Lauren B. Davis
Data to Donations: Towards In-Kind Food Donation Prediction across Two Coasts. GHTC 2021: 281-288 - [c21]Erik T. Rosenstrom, Julie S. Ivy, Maria E. Mayorga, Julie L. Swann, Buse Eylul Oruc
High-Quality Masks Reduce Covid-19 Infections and Death in the US. WSC 2021: 1-11 - 2020
- [c20]Breanna P. Swan, Siddhartha Nambiar
Evaluating Diabetic Retinopathy Screening Interventions in a Microsimulation Model. WSC 2020: 944-955
2010 – 2019
- 2019
- [j12]Joseph Agor, Osman Y. Özaltin
The value of missing information in severity of illness score development. J. Biomed. Informatics 97 (2019) - [c19]Ali Jazayeri, Muge Capan
Simulating Uncertainty of Early Warning Scores in Sepsis Detection. BCB 2019: 543 - [c18]Chen Lin, Julie S. Ivy, Min Chi:
Multi-layer Facial Representation Learning for Early Prediction of Septic Shock. IEEE BigData 2019: 840-849 - [c17]Yuan Zhang, Xi Yang, Julie S. Ivy, Min Chi:
Time-aware Adversarial Networks for Adapting Disease Progression Modeling. ICHI 2019: 1-11 - [c16]Yuan Zhang, Xi Yang, Julie S. Ivy, Min Chi:
ATTAIN: Attention-based Time-Aware LSTM Networks for Disease Progression Modeling. IJCAI 2019: 4369-4375 - [c15]Lena Abu-El-Haija, Julie S. Ivy, Osman Y. Özaltin
The Effect of the Distribution of the Inverse Growth Rate on Pancreatic Cancer Progression. WSC 2019: 1044-1054 - 2018
- [j11]Irem Sengul Orgut
Robust optimization approaches for the equitable and effective distribution of donated food. Eur. J. Oper. Res. 269(2): 516-531 (2018) - [c14]Chen Lin, Yuan Zhang, Julie S. Ivy, Muge Capan
Early Diagnosis and Prediction of Sepsis Shock by Combining Static and Dynamic Information Using Convolutional-LSTM. ICHI 2018: 219-228 - [c13]Farzaneh Khoshnevisan, Julie S. Ivy, Muge Capan
Recent Temporal Pattern Mining for Septic Shock Early Prediction. ICHI 2018: 229-240 - [c12]Nisha Nataraj, Julie S. Ivy, Jeanne Huddleston, Ryan Arnold, Muge Capan:
What's in a Definition? A simulation Framework for Modeling sepsis Interventions using Electronic Health Records. WSC 2018: 2483-2494 - 2017
- [j10]Karen Hicklin, Julie S. Ivy, Anita R. Vila-Parrish:
Case Article - A Prescription for Budget Woes at Gracious University Hospital. INFORMS Trans. Educ. 17(3): 107-109 (2017) - [j9]Karen Hicklin, Julie S. Ivy, Anita R. Vila-Parrish:
Case - A Prescription for Budget Woes at Gracious University Hospital. INFORMS Trans. Educ. 17(3): 110-115 (2017) - [c11]Yuan Zhang, Chen Lin, Min Chi, Julie S. Ivy, Muge Capan, Jeanne M. Huddleston:
LSTM for septic shock: Adding unreliable labels to reliable predictions. IEEE BigData 2017: 1233-1242 - 2015
- [j8]Amy Craig Reamer, Julie S. Ivy, Anita R. Vila-Parrish, Robert E. Young:
Understanding the evolution of mathematics performance in primary education and the implications for STEM learning: A Markovian approach. Comput. Hum. Behav. 47: 4-17 (2015) - [c10]Karen Hicklin, Julie S. Ivy, James R. Wilson, Evan R. Myers:
Using percentile matching to simulate labor progression and the effect of labor duration on birth complications. WSC 2015: 3104-3105 - 2014
- [j7]Hamed Yarmand, Julie S. Ivy, Brian T. Denton, Alun L. Lloyd:
Optimal two-phase vaccine allocation to geographically different regions under uncertainty. Eur. J. Oper. Res. 233(1): 208-219 (2014) - [c9]Pegah Pooya, Julie S. Ivy, Lukasz Mazur, Katharin Deschesne, Prithima Mosaly, Gregg Tracton, Nishant Singh:
Assessing the reliability of the radiation therapy care delivery process using discrete event simulation. WSC 2014: 1233-1244 - [c8]Shadi Hassani Goodarzi, Kendall McKenzie, Nisha Nataraj, Julie S. Ivy, Maria E. Mayorga
A framework for modeling the complex interaction between breast cancer and diabetes. WSC 2014: 1245-1256 - [c7]Karen Hicklin, Julie S. Ivy, Evan R. Myers, Vidyadhar G. Kulkarni, Meera Viswanathan:
Simulation of labor: a study of the relationship between cesarean section rates and the time spent in labor. WSC 2014: 1269-1280 - 2013
- [j6]Hamed Yarmand, Julie S. Ivy:
Analytic solution of the susceptible-infective epidemic model with state-dependent contact rates and different intervention policies. Simul. 89(6): 703-721 (2013) - [j5]Hamed Yarmand, Julie S. Ivy, Stephen D. Roberts:
Identifying optimal mitigation strategies for responding to a mild influenza epidemic. Simul. 89(11): 1400-1415 (2013) - [j4]Hamed Yarmand, Julie S. Ivy:
Optimal intervention strategies for an epidemic: A household view. Simul. 89(12): 1505-1522 (2013) - [c6]Jeremy J. Tejada, Kathleen M. Diehl, Julie Simmons Ivy, James R. Wilson, Russell E. King, Matthew J. Ballan, Michael G. Kay
Combined DES/SD simulaton model of breast cancer screening for older women: An overview. WSC 2013: 41-53 - [c5]Gokce Akin, Julie S. Ivy, Todd R. Huschka, Thomas Rohleder, Yariv N. Marmor
Capacity management and patient scheduling in an outpatient clinic using discrete event simulation. WSC 2013: 2215-2226 - 2010
- [j3]Michael E. Kuhl, Julie Simmons Ivy, Emily K. Lada, Natalie M. Steiger, Mary Ann Flanigan Wagner, James R. Wilson:
Univariate input models for stochastic simulation. J. Simulation 4(2): 81-97 (2010) - [c4]Hamed Yarmand, Julie S. Ivy, Stephen D. Roberts, Mary W. Bengtson, Neal M. Bengtson
Cost-effectiveness analysis of vaccination and self-isolation in case of H1N1. WSC 2010: 2199-2210
2000 – 2009
- 2009
- [c3]Michael E. Kuhl, Emily K. Lada, Mary Ann Flanigan Wagner, Julie Simmons Ivy, Natalie M. Steiger, James R. Wilson:
Introduction to Modeling and Generating Probabilistic Input Processes for Simulation. WSC 2009: 184-202 - [c2]Sharolyn Wynter, Julie Simmons Ivy:
Simulating Public Health Emergency Response: A Case Study of the 2004 North Carolina State Fair E. Coli Outbreak. WSC 2009: 1957-1968 - 2008
- [j2]Lisa M. Maillart
Assessing Dynamic Breast Cancer Screening Policies. Oper. Res. 56(6): 1411-1427 (2008) - [c1]Ana R. Vila-Parrish, Julie Simmons Ivy, Russell E. King
A simulation-based approach for inventory modeling of perishable pharmaceuticals. WSC 2008: 1532-1538 - 2005
- [j1]Julie S. Ivy, Stephen M. Pollock:
Marginally monotonic maintenance policies for a multi-state deteriorating machine with probabilistic monitoring, and silent failures. IEEE Trans. Reliab. 54(3): 489-497 (2005)
Coauthor Index
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