Prediction of Hospitalization Using Machine Learning for Emergency Department Patients.

Autor: Feretzakis G; School of Science and Technology, Hellenic Open University, Patras, Greece.; Department of Quality Control, Research and Continuing Education, Sismanogleio General Hospital, Marousi, Greece.; IT department, Sismanogleio General Hospital, Marousi, Greece., Sakagianni A; Intensive Care Unit, Sismanogleio General Hospital, Marousi, Greece., Loupelis E; IT department, Sismanogleio General Hospital, Marousi, Greece., Kalles D; School of Science and Technology, Hellenic Open University, Patras, Greece., Panteris V; Gastroenterology Department, Sismanogleio General Hospital, Marousi, Greece., Tzelves L; Second Department of Urology, National and Kapodistrian University of Athens, Sismanogleio General Hospital, Marousi, Greece., Chatzikyriakou R; Hematology Laboratory, Sismanogleio General Hospital, Marousi, Greece., Trakas N; Biochemistry Department, Sismanogleio General Hospital, Marousi, Greece., Kolokytha S; Emergency Department, Sismanogleio General Hospital, Marousi, Greece., Batiani P; Emergency Department, Sismanogleio General Hospital, Marousi, Greece., Rakopoulou Z; Administration, Sismanogleio General Hospital, Marousi, Greece., Tika A; Administration, Sismanogleio General Hospital, Marousi, Greece., Petropoulou S; IT department, Sismanogleio General Hospital, Marousi, Greece., Dalainas I; Administration, Sismanogleio General Hospital, Marousi, Greece., Kaldis V; Emergency Department, Sismanogleio General Hospital, Marousi, Greece.
Jazyk: angličtina
Zdroj: Studies in health technology and informatics [Stud Health Technol Inform] 2022 May 25; Vol. 294, pp. 145-146.
DOI: 10.3233/SHTI220422
Abstrakt: 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: MEDLINE