Prediction of Hospitalization Using Machine Learning for Emergency Department Patients
- Resource Type
- Authors
- Georgios, Feretzakis; Aikaterini, Sakagianni; Evangelos, Loupelis; Dimitris, Kalles; Vasileios, Panteris; Lazaros, Tzelves; Rea, Chatzikyriakou; Nikolaos, Trakas; Stavroula, Kolokytha; Polyxeni, Batiani; Zoi, Rakopoulou; Aikaterini, Tika; Stavroula, Petropoulou; Ilias, Dalainas; Vasileios, Kaldis
- Source
- Studies in health technology and informatics. 294
- Subject
- Hospitalization
Machine Learning
ROC Curve
Humans
Emergency Service, Hospital
Retrospective Studies
- Language
- ISSN
- 1879-8365
The objective of this study was to evaluate the predictive capability of five machine learning models regarding the admission or discharge of emergency department patients. A Random Forest classifier outperformed other models with respect to the area under the receiver operating characteristic curve (AUC ROC).