Prediction of Hospitalization Using Machine Learning for Emergency Department Patients
Autor: | 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 |
---|---|
Rok vydání: | 2022 |
DOI: | 10.3233/shti220422 |
Popis: | 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). |
Databáze: | OpenAIRE |
Externí odkaz: |