Exploratory Clustering for Emergency Department Patients

Exploratory Clustering for Emergency Department Patients

Emergency department (ED) overcrowding is an increasing global problem raising safety concerns for the patients. Elaborating an effective triage system that properly separates patients requiring hospital admission remains difficult. The objective of this study was to compare a clustering-related tec...

Full description

Bibliographic Details
Main Authors: Batiani, P. (Author), Chatzikyriakou, R. (Author), Dalainas, I. (Author), Feretzakis, G. (Author), Kaldis, V. (Author), Kalles, D. (Author), Kolokytha, S. (Author), Loupelis, E. (Author), Panteris, V. (Author), Petropoulou, S. (Author), Rakopoulou, Z. (Author), Sakagianni, A. (Author), Tika, A. (Author), Trakas, N. (Author), Tzelves, L. (Author)
Format: Article
Language:English
Published: NLM (Medline) 2022
Subjects:
adult
article
clustering
controlled study
crowding (area)
emergency department
emergency ward
hospital admission
human
k means clustering
k-means
machine learning
Machine learning
patient triage
unsupervised learning
unsupervised machine learning
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items