Time series model for forecasting the number of new admission inpatients

Time series model for forecasting the number of new admission inpatients

Abstract Background Hospital crowding is a rising problem, effective predicting and detecting managment can helpful to reduce crowding. Our team has successfully proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural networ...

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Bibliographic Details
Main Authors: Lingling Zhou, Ping Zhao, Dongdong Wu, Cheng Cheng, Hao Huang
Format: Article
Language:English
Published: BMC 2018-06-01
Series:BMC Medical Informatics and Decision Making
Subjects:
New admission inpatients
Time series forecasting
SARIMA model
NARNN model
Hybrid model
Online Access:http://link.springer.com/article/10.1186/s12911-018-0616-8

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