A Hybrid Process Mining Framework for Automated Simulation Modelling for Healthcare
| Autor: | Waleed Abo-Hamad, Mohammed Mesabbah, Susan McKeever |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
021103 operations research Process modeling business.industry Computer science Simulation modelling process mining 0211 other engineering and technologies Complex system Process mining health 02 engineering and technology Business process modeling simulation Automation 020901 industrial engineering & automation machine learning Health care Information system business Software engineering predictive simulation process modelling Music |
| Zdroj: | Conference papers WSC |
| Popis: | Advances in data and process mining algorithms combined with the availability of sophisticated information systems have created an encouraging environment for innovations in simulation modelling. Researchers have investigated the integration between such algorithms and business process modelling to facilitate the automation of building simulation models. These endeavors have resulted in a prototype termed Auto Simulation Model Builder (ASMB) for DES models. However, this prototype has limitations that undermine applying it on complex systems. This paper presents an extension of the ASMB framework previously developed by authors adopted for healthcare systems. The proposed framework offers a comprehensive solution for resources handling to support complex decision-making processes around hospital staff planning. The framework also introduces a machine learning real-time data-driven prediction approach for system performance using advanced activity blocks for the auto-generated model, based on live-streams of patient data. This prediction can be useful for both single and multiple healthcare units management. |
| Databáze: | OpenAIRE |
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