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Agent-oriented Decision Support System for Business Processes Management with Genetic Algorithm Optimization: an
Emilio Sulis1, Pietro Terna2, Antonio Di Leva3
1Computer Science Department, University of Torino, Torino, Italy. emilio.sulis@unito.it.
This study introduces an agent-oriented decision support system for hospital emergency departments. It uses agent-based modeling and genetic algorithms to improve patient management and healthcare processes.
Area of Science:
- Health Informatics
- Artificial Intelligence in Healthcare
- Management Science
Background:
- Agent-based approaches are increasingly used in medical administration.
- Business Process Management (BPM) heavily relies on discrete-event modeling and simulation.
- Integrating management science, agent-based modeling, and AI offers potential for healthcare improvement.
Purpose of the Study:
- To propose a medical agent-oriented decision support system.
- To apply this system to a hospital emergency department.
- To explore intelligent patient management using genetic algorithms.
Main Methods:
- Utilized the NetLogo multi-agent programmable modeling environment.
- Developed a 3D model representing healthcare processes with agents (patients, staff).
- Applied genetic algorithms for optimizing patient selection in admission procedures.
Main Results:
- Successfully demonstrated a clear representation of healthcare processes in a 3D environment.
- Enabled traditional what-if scenario analysis for hospital operations.
- Showcased encouraging results for intelligent patient management via genetic algorithms.
Conclusions:
- Agent-oriented methodologies show promise for healthcare management.
- The proposed system effectively models and analyzes emergency department processes.
- Genetic algorithms can enhance patient admission and selection criteria.
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