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ORCIDOwen Molloy
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2020 – today
- 2023
[j7]Mary Conlon
, Owen Molloy:
Modelling a Computed Tomography service using mixed Operational Research methods. J. Simulation 17(5): 544-556 (2023)- 2022
- [j6]Mary Conlon, Owen Molloy:
Learning to See: Using Mixed or Methods to Model Radiology Staff Workload and Support Decision Making in CT. SN Comput. Sci. 3(5): 361 (2022) - 2020
- [c27]Mary Conlon, Owen Molloy, Nora ZolzerBryce:
Driving the Bus: A Radiology Case Study Utilizing Rich Picture Diagramming and CATWOE to Capture Staff Perceptions and Inform Service Improvement Scenarios. KMIS 2020: 88-99
2010 – 2019
- 2019
- [c26]Mary Conlon, Owen Molloy:
Knowledge Management in Healthcare: Information Requirements When Creating a Decision Support Tool in Radiology. KMIS 2019: 317-324 - [c25]Conor McCrossan, Owen Molloy:
Measuring Individuals' Knowledge, Attitude and Behaviour on Specific Ocean Related Topics. KMIS 2019: 325-332 - 2018
- [c24]Mahmoud Elbattah, Owen Molloy:
ML-Aided Simulation: A Conceptual Framework for Integrating Simulation Models with Machine Learning. SIGSIM-PADS 2018: 33-36 - [c23]Bhakti Stephan Onggo, Navonil Mustafee, Philip Andi Smart, Angel A. Juan, Owen Molloy:
Symbiotic simulation System: Hybrid Systems Model Meets Big Data Analytics. WSC 2018: 1358-1369 - [c22]Mahmoud Elbattah, Owen Molloy, Bernard P. Zeigler:
Designing Care pathways using simulation Modeling and Machine Learning. WSC 2018: 1452-1463 - 2017
- [c21]Mahmoud Elbattah, Owen Molloy:
Clustering-Aided Approach for Predicting Patient Outcomes with Application to Elderly Healthcare in Ireland. AAAI Workshops 2017 - [c20]Mahmoud Elbattah, Owen Molloy:
Data-driven patient segmentation using K-means clustering: the case of hip fracture care in Ireland. ACSW 2017: 60:1-60:8 - [c19]Mahmoud Elbattah, Owen Molloy:
Learning about systems using machine learning: Towards more data-driven feedback loops. WSC 2017: 1539-1550 - 2016
- [j5]Alejandro Vera Baquero, Ricardo Colomo Palacios, Owen Molloy:
Real-time business activity monitoring and analysis of process performance on big-data domains. Telematics Informatics 33(3): 793-807 (2016) - [c18]Mahmoud Elbattah, Owen Molloy:
Using Machine Learning to Predict Length of Stay and Discharge Destination for Hip-Fracture Patients. IntelliSys (1) 2016: 207-217 - [c17]Mahmoud Elbattah, Owen Molloy:
Coupling Simulation with Machine Learning: A Hybrid Approach for Elderly Discharge Planning. SIGSIM-PADS 2016: 47-56 - 2015
- [c16]Alejandro Vera Baquero, Ricardo Colomo Palacios, Owen Molloy:
Measuring and Querying Process Performance in Supply Chains: An Approach for Mining Big-Data Cloud Storages. CENTERIS/ProjMAN/HCist 2015: 1026-1034 - [c15]Mahmoud Elbattah, Owen Molloy:
Towards Improving Modeling and Simulation of Clinical Pathways: Lessons Learned and Future Insights. SIMULTECH 2015: 508-514 - 2013
- [j4]Alejandro Vera Baquero, Ricardo Colomo Palacios, Owen Molloy:
Business Process Analytics Using a Big Data Approach. IT Prof. 15(6): 29-35 (2013) - 2012
- [j3]Sean Kennedy, Owen Molloy, Robert Stewart, Paul Jacob, Maria Maleshkova, Frank Doheny:
A Semantically Automated Protocol Adapter for Mapping SOAP Web Services to RESTful HTTP Format to Enable the Web Infrastructure, Enhance Web Service Interoperability and Ease Web Service Migration. Future Internet 4(2): 372-395 (2012) - [c14]Alejandro Vera Baquero, Owen Molloy:
A Framework to Support Business Process Analytics. KMIS 2012: 321-332 - [c13]Alejandro Vera Baquero, Owen Molloy:
Integration of Event Data from Heterogeneous Systems to Support Business Process Analysis. IC3K 2012: 440-454 - 2011
- [j2]Sean Kennedy, Robert Stewart, Paul Jacob, Owen Molloy:
StoRHm: a protocol adapter for mapping SOAP based Web Services to RESTful HTTP format. Electron. Commer. Res. 11(3): 245-269 (2011)
2000 – 2009
- 2009
- [j1]Claire Costello, Owen Molloy:
A process model to support automated measurement and detection of out-of-bounds events in a hospital laboratory process. J. Theor. Appl. Electron. Commer. Res. 4(2): 31-30 (2009) - 2008
- [c12]Claire Costello, Owen Molloy:
Towards a Semantic Framework for Business Activity Monitoring and Management. AAAI Spring Symposium: AI Meets Business Rules and Process Management 2008: 17-27 - 2007
- [c11]Brian Shields, Owen Molloy:
Using Description Logic and Rules to Determine XML Access Control. DEXA Workshops 2007: 718-724 - [c10]Claire Costello, Owen Molloy:
Building a Process Performance Model for Business Activity Monitoring. ISD (1) 2007: 237-248 - [c9]Brian Shields, Owen Molloy:
Securing Systems Intelligently: The Logical Approa. ISD (2) 2007: 753-766 - 2006
- [c8]Claire Costello, Weston Fleming, Owen Molloy, Gerard Lyons, Jim Duggan:
iWISE: A Framework for Providing Distributed Process Visibility Using an Event-Based Process Modelling Approach. ICEIS (3) 2006: 224-233 - [c7]Brian Shields, Owen Molloy, Gerard Lyons, Jim Duggan:
Using semantic rules to determine access control for web services. WWW 2006: 913-914 - 2005
- [c6]Claire Costello, Owen Molloy, Gerard Lyons, Jim Duggan:
Using Event-Based Process Modelling to Support Six Sigma Quality. DEXA Workshops 2005: 926-930 - [c5]Brian Shields, Owen Molloy, Gerard Lyons, Jim Duggan:
Securing Web Services Using Semantic Web Technologies. Industrial Applications of Semantic Web 2005: 261-273 - 2004
- [c4]Claire Costello, Owen Molloy:
Orchestrating supply chain interactions using emerging process description languages and business rules. ICEC 2004: 21-30 - [c3]Brian Shields, Owen Molloy:
Dynamic Configuration of Collaboration in Networked Organisations. Virtual Enterprises and Collaborative Networks 2004: 205-214 - 2003
- [c2]Claire Costello, Owen Molloy:
A Rules Based Approach to Business Process Management. International Conference on Internet Computing 2003: 339-345 - [c1]Brian Shields, Owen Molloy:
An Agent Based Approach to Enterprise Application Integration. International Conference on Internet Computing 2003: 361-370
Coauthor Index
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