Forecasting daily emergency department arrivals using high-dimensional multivariate data: a feature selection approach

Forecasting daily emergency department arrivals using high-dimensional multivariate data: a feature selection approach

Abstract Background and objective Emergency Department (ED) overcrowding is a chronic international issue that is associated with adverse treatment outcomes. Accurate forecasts of future service demand would enable intelligent resource allocation that could alleviate the problem. There has been cont...

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Bibliographic Details
Main Authors: Jalmari Tuominen, Francesco Lomio, Niku Oksala, Ari Palomäki, Jaakko Peltonen, Heikki Huttunen, Antti Roine
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Emergency department
Crowding
Feature selection
Machine learning
Time series forecasting
Statistical learning
Online Access:https://doi.org/10.1186/s12911-022-01878-7

Internet

https://doi.org/10.1186/s12911-022-01878-7

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