University of Twente Student Theses
Predicting overcrowding in the acute care domain using random forest regression
Tokarczyk, F. (2020) Predicting overcrowding in the acute care domain using random forest regression.
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| Abstract: | Crowding is a phenomenon that occurs more frequently within the facilities of the acute care domain. Acute care providers are interested in; means to quantify crowding, potential predictors of crowding, and a model to forecast crowding. This information can help the facilities to plan accordingly to future acute care demand. In this research, we focus on these topics and provide a machine learning model for an emergency department and general practitioner's post in Gelderland. This model predicts the total daily visitors to the facilities based on a variety of external variables, such as weather data, pollen data, et cetera and provides an overview of the most important variables in the models. |
| Item Type: | Essay (Master) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 50 technical science in general, 54 computer science, 85 business administration, organizational science |
| Programme: | Industrial Engineering and Management MSc (60029) |
| Link to this item: | https://purl.utwente.nl/essays/85274 |
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