Simulation and big data: A way to discover unusual knowledge in emergency departments: Work-in-progress paper

Proceedings - 2014 International Conference on Future Internet of Things and Cloud, FiCloud 2014

Volumn , Issue , 2014, Pages 367-372

  Bruballa, Eva ^a   Taboada, Manel ^a   Cabrera, Eduardo ^a   Rexachs, Dolores ^a   Luque, Emilio ^a  

^a UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

Author keywords

Agent Based Modeling and Simulation (ABMS); Big Data; Data Mining (DM); Decision Support Systems (DSS); Emergency Department (ED); Knowledge Discovery

Indexed keywords

AUTONOMOUS AGENTS; BIG DATA; COMPUTATIONAL METHODS; DECISION SUPPORT SYSTEMS; EMERGENCY ROOMS; QUALITY OF SERVICE;

AGENT-BASED MODELING AND SIMULATION; DECISION SUPPORT SYSTEM (DSS); EMERGENCY DEPARTMENTS; HIGH PERFORMANCE COMPUTING; HOSPITAL EMERGENCY DEPARTMENTS; LARGE AMOUNTS; MASSIVE DATA; WORK IN PROGRESS;

DATA MINING;

EID: 84922564039     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FiCloud.2014.65     Document Type: Conference Paper

References (21)

1. A. M. Mancilla, "Simulation: A tool for the study of real systems", Ingenieriá y Desarrollo, Universidad del Norte, vol. 6, pp.104-112, 1999. Available: http://rcientificas.uninorte.edu.co/index.php/ingenieria/article/view/2226/1443
2. J. Pavón, M. Arroyo, S. Hassan & C. Sansores, "Simulation of social systems with software agents", CMPI-2006, Actas del Campus Multidisciplinar en Percepcion e Inteligencia, vol. 1, pp. 389-400, 2006. Available: http://samer.hassan.name/files/CMPI
3. L. R. Izquierdo, J.M. Galán, J.I. Santos & R. Del Olmo, "Modeling complex systems using agent-based simulation and system dynamics", "Modelado de sistemas complejos mediante simulación basada en agentes y mediante dinámica de sistemas", Empiria: Revista de metodologiá de ciencias sociales, vol. 16, pp. 85-112, 2008.
4. M. Taboada, E. Cabrera, M. L. Iglesias, F. Epelde & E. Luque, "An agent-based decision support system for hospitals emergency departments", Procedia Computer Science, vol. 4, pp. 1870-1879, ICCS 2011.
5. M. Taboada, E. Cabrera & E. Luque, "Modeling, simulation and optimization of resources management in hospital emergency departments using the agent-based approach", Advances in Computational Modeling Research, pp.1-31, 2013.
6. M. Taboada, E. Cabrera, F. Epelde , M. L. Iglesias & E. Luque, "Using an agent-based simulation for predicting the effects of patients derivation policies in emergency departments", Procedia Computer Science, vol. 18, pp. 641-650, ICCS 2013.
7. E. Cabrera, M. Taboada, M. L. Iglesias, F. Epelde & E. Luque, "Optimization of healthcare emergency departments by agent-based simulation", Procedia Computer Science, vol. 4, pp. 1880-1889, ICCS 2011.
8. E. Cabrera, M. Taboada, M. L. Iglesias, F. Epelde & E. Luque, "Simulation optimization for healthcare emergency departments", Procedia Computer Science, vol. 9, pp. 1464-1473, ICCS 2012.
9. A. Choudhary, Northwestern University, USA, Keynote Speaker: "Big Data, exascale systems and knowledge discovery-The next frontier for HPC, Euro-Par Conference, August 2013. Available: http://www.europar2013.org/upload/Dokumente/Euro-Par-2013-Keynote-Choudhary
10. E. Bonabeau, "Big Data and the bright future of simulation (The case of agent-based modeling)", Program Winter Simulation Conference 2013. Available: https://ssl.linklings.net/conferences/wsc/wsc2013-program/views/by-ro om.html
11. N. Lavrac, "Selected techniques for data mining in medicine", Artificial Intelligence in Medicine, vol.16, pp. 3-23, 1999.
12. H. Chye, & G. Tan, "Data mining applications in healthcare", Journal of Healthcare Information Management, vol. 9, no. 2, 2005.
13. C. C. Yang, W. T. Lin, H. M. Chen & Y.H. Shi, "Improving scheduling of emergency physicians using data mining analysis", Expert Systems with Applications, vol. 36, no. 2, pp.3378-3387, 2009.
14. A. Ceglowski, L. Churilov & J. Wassertheil, "Knowledge discovery through mining emergency department data", Proceedings of the 38th Annual Hawaii International Conference on System Sciences, IEEE, pp. 142c-142c, 2005.
15. A. Ceglowski, L. Churilov & J. Wassertheil, "Combining data mining and discrete event simulation for a value-added view of a hospital emergency department", Journal of the Operational Research Society, pp. 246-255, 2006.
16. L. Grigull & W. M. Lechner, "Supporting diagnostic decisions using hybrid and complementary data mining applications: a pilot study in the pediatric emergency department", Pediatric research, vol.71, no. 6, pp. 725-31, 2012.
17. W. T. Lin, Y. C. Wu, J. S. Zheng & M. Y. Chen, "Analysis by data mining in the emergency medicine triage database at a Taiwanese regional hospital", Expert Systems with Applications, vol. 38, no. 9, pp. 11078-11084, 2011.
18. N. Jay, G. Nuemi, M. Gadreau & C. Quantin, "A data mining approach for grouping and analiyzing trajectories of care using claim data: the example of breast cancer", BMC Medical Informatics and Decision Making, 13: 130, 2013. Available: http://www.biomedcentral.com/1472-6947/13/130
19. I. H. Witten & E. Frank, "Data mining: Practical machine learning tools and techniques", Morgan Kaufmann, 2005.
20. Mathematics and Computer Science. Tools and technology for solving critical scientific problems. Argonne National Laboratory. http://www.mcs.anl.gov/group/data-intensive-science
21. Cloudera: The platform for Big Data and the leading solution for Apache Hadoop in the Enterprise. http://www.cloudera.com/content/cloudera/en/home.html