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Adele H. Marshall
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2020 – today
- 2023
- [c29]Aleksandar Novakovic, Adele H. Marshall, Carolyn McGregor
, Nadja Bressan, Kate McAllister, Emily Courcier:
Using machine learning to improve bovine tuberculosis control in herd level outbreaks. EMBC 2023: 1-4 - [c28]Miao Hu
, Zhiwei Lin, Adele H. Marshall
:
Expanding Domain-Specific Knowledge Graphs with Unknown Facts. NLDB 2023: 352-364 - [c27]Miao Hu
, Zhiwei Lin, Adele H. Marshall
:
Knowledge Graph Representation Learning via Generated Descriptions. NLDB 2023: 365-378 - 2022
- [j15]Adele H. Marshall, Aleksandar Novakovic:
Process Mining the Performance of a Real-Time Healthcare 4.0 Systems Using Conditional Survival Models. Algorithms 15(6): 196 (2022) - [j14]Laura M. Boyle
, Adele H. Marshall, Mark Mackay:
A framework for developing generalisable discrete event simulation models of hospital emergency departments. Eur. J. Oper. Res. 302(1): 337-347 (2022) - [j13]Aleksandar Novakovic, Adele H. Marshall:
The CP-ABM approach for modelling COVID-19 infection dynamics and quantifying the effects of non-pharmaceutical interventions. Pattern Recognit. 130: 108790 (2022) - [c26]Kyle McBride, Aleksandar Novakovic, Adele H. Marshall, Emily Courcier:
Knowledge Discovery of Bovine Tuberculosis in the Eurasian Badger using Machine Learning Techniques. CSCI 2022: 362-367 - 2021
- [j12]Hannah J. Mitchell, Adele H. Marshall
, Mariangela Zenga:
A joint likelihood approach to the analysis of length of stay data utilising the continuous-time hidden Markov model and Coxian phase-type distribution. J. Oper. Res. Soc. 72(11): 2529-2541 (2021) - [c25]Aleksandar Novakovic, Adele H. Marshall, Carolyn McGregor
:
Knowledge Discovery of the Delays Experienced in Reporting COVID-19 Confirmed Positive Cases Using Time to Event Models. DS 2021: 183-193 - [c24]Nadezda Demidova
, Aleksandar Novakovic, Adele H. Marshall:
Optimizing the Belfast Bike Sharing Scheme. IntelliSys (2) 2021: 586-599 - 2020
- [j11]Aleksandar Novakovic, Adele H. Marshall
:
Introducing the DM-P approach for analysing the performances of real-time clinical decision support systems. Knowl. Based Syst. 198: 105877 (2020) - [j10]Nicola-Ann Stevens
, Myra Lydon
, Adele H. Marshall
, Su Taylor
:
Identification of Bridge Key Performance Indicators Using Survival Analysis for Future Network-Wide Structural Health Monitoring. Sensors 20(23): 6894 (2020)
2010 – 2019
- 2019
- [c23]Adele H. Marshall
, Aleksandar Novakovic:
Analysing the Performance of a Real-Time Healthcare 4.0 System using Shared Frailty Time to Event Models. CBMS 2019: 622-627 - 2018
- [j9]Charles J. Gillan, Aleksandar Novakovic, Adele H. Marshall
, Murali Shyamsundar
, Dimitrios S. Nikolopoulos
:
Expediting assessments of database performance for streams of respiratory parameters. Comput. Biol. Medicine 100: 186-195 (2018) - [c22]Caoimhe M. Carbery, Roger F. Woods
, Adele H. Marshall
:
A Bayesian network based learning system for modelling faults in large-scale manufacturing. ICIT 2018: 1357-1362 - 2016
- [j8]Giulio Napolitano
, Adele H. Marshall
, Peter Hamilton, Anna T. Gavin:
Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction. Artif. Intell. Medicine 70: 77-83 (2016) - [c21]Caoimhe M. Carbery, Adele H. Marshall
, Roger F. Woods
:
Proposing the Deep Dynamic Bayesian Network as a Future Computer Based Medical System. CBMS 2016: 227-228 - [c20]Andrew S. Gordon, Adele H. Marshall
, Mariangela Zenga:
A Discrete Conditional Phase-Type Model Utilising a Survival Tree for the Identification of Elderly Patient Cohorts and Their Subsequent Prediction of Length of Stay in Hospital. CBMS 2016: 259-264 - [c19]Christopher John Steele, Adele H. Marshall
, Anne Kouvonen
, Frank Kee, Reijo Sund
:
Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners. CBMS 2016: 271-272 - 2015
- [c18]Rebecca Rollins, Adele H. Marshall
, Eibhlin McLoone, Sarah Chamney:
Discrete Conditional Phase-Type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity. CBMS 2015: 250-255 - 2014
- [j7]Adele H. Marshall
, Barry Shaw:
Computational learning of the conditional phase-type (C-Ph) distribution. Comput. Manag. Sci. 11(1-2): 139-155 (2014) - 2012
- [j6]Paul R. Harper, Vincent A. Knight, Adele H. Marshall
:
Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities. Eur. J. Oper. Res. 219(3): 522-530 (2012) - [c17]Adele H. Marshall
, Kieran Payne, Karen J. Cairns, Stan Craig, Emma McCall:
Modelling the development of late onset sepsis and length of stay using discrete conditional survival models with a classification tree component. CBMS 2012: 1-6 - [c16]Aidan Fitzgerald, Salissou Moutari, Adele H. Marshall
:
Modelling traffic dynamics in motorway networks. ITSC 2012: 1834-1839 - 2011
- [j5]Karen J. Cairns, Adele H. Marshall
, Frank Kee:
Using simulation to assess cardiac first-responder schemes exhibiting stochastic and spatial complexities. J. Oper. Res. Soc. 62(6): 982-991 (2011) - 2010
- [c15]Adele H. Marshall
, Laura A. Hill, Frank Kee:
Continuous Dynamic Bayesian networks for predicting survival of ischaemic heart disease patients. CBMS 2010: 178-183 - [c14]Adele H. Marshall
, Laura A. Hill:
Clustering gene expression data using Coxian phase-type survival. IEEE Conf. of Intelligent Systems 2010: 179-184
2000 – 2009
- 2009
- [j4]Adele H. Marshall
, Mariangela Zenga:
Simulating Coxian phase-type distributions for patient survival. Int. Trans. Oper. Res. 16(2): 213-226 (2009) - [c13]Giulio Napolitano, Alejandra N. González-Beltrán, Colin Fox, Adele H. Marshall, Anthony Finkelstein, Peter McCarron:
Biomedical Ontologies and Grid Computing - As New Resources for Cancer Registries. HEALTHINF 2009: 512-517 - [c12]Adele H. Marshall
, Lisa McCrink
:
Discrete Conditional Phase-type model (DC_Ph) for patient waiting time with a logistic regression component to predict patient admission to hospital. CBMS 2009: 1-6 - 2008
- [c11]Adele H. Marshall
, Barry Shaw:
Modeling the Survival of Hip Fracture Patients Using a Conditional Phase-Type Distribution. CBMS 2008: 518-523 - [c10]Andrea Rainey, Karen Carins, Adele H. Marshall
, Michael Quinn, Gerard Savage, Damian Fogarty
:
The Effects of Anti-Hypertensive Drugs Evaluated Using Markov Modelling for Northern Ireland Chronic Kidney Disease Patients. CBMS 2008: 530-535 - 2007
- [j3]Barry Shaw, Adele H. Marshall
:
Modelling the flow of congestive heart failure patients through a hospital system. J. Oper. Res. Soc. 58(2): 212-218 (2007) - [c9]Adele H. Marshall
, Louise Burns:
A Bayesian Network Hybrid Model for Representing Accident and Emergency Waiting Times. CBMS 2007: 91-96 - 2006
- [j2]Barry Shaw, Adele H. Marshall
:
Modeling the Health Care Costs of Geriatric Inpatients. IEEE Trans. Inf. Technol. Biomed. 10(3): 526-532 (2006) - [c8]Adele H. Marshall
, Karen J. Cairns, Frank Kee, Michael J. Moore, Andrew J. Hamilton, A. A. Jennifer Adgey:
A Monte Carlo Simulation Model to Assess Volunteer Response Times in a Public Access Defibrillation Scheme in Northern Ireland. CBMS 2006: 783-788 - [c7]Adele H. Marshall
, Ronan Donaghy:
Intelligent Patient Management using Dynamic Models of Clinical Variables. CBMS 2006: 805-812 - 2005
- [j1]Christos Vasilakis
, Adele H. Marshall
:
Modelling nationwide hospital length of stay: opening the black box. J. Oper. Res. Soc. 56(7): 862-869 (2005) - [c6]Barry Shaw, Adele H. Marshall
:
A Bayesian Approach to Modelling Inpatient Expenditure. CBMS 2005: 491-496 - [c5]Karen J. Cairns, Adele H. Marshall, Frank Kee:
A Public Access Defibrillation Trial in Urban and Rural Communities in Northern Ireland: Developing the Roster Model. CBMS 2005: 497-502 - [c4]Adele H. Marshall
, Roy Sterritt
:
Clustering Gene Expression Data using Continuous Markov Models. CSB Workshops 2005: 314-321 - 2002
- [c3]Adele H. Marshall
, David A. Bell, Roy Sterritt
:
Handling Uncertainty in a Medical Study of Dietary Intake During Pregnancy. Soft-Ware 2002: 206-216 - 2000
- [c2]Adele H. Marshall
, Sally I. McClean, Mary Shapcott, Peter H. Millard:
Learning Dynamic Bayesian Belief Networks Using Conditional Phase-Type Distributions. PKDD 2000: 516-523 - [c1]Roy Sterritt, Adele H. Marshall, C. Mary Shapcott, Sally I. McClean:
Exploring dynamic Bayesian belief networks for intelligent fault management systems. SMC 2000: 3646-3652
Coauthor Index
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