Cargando…
How to improve the future efficiency of Covid-19 treatment centers? A hybrid framework combining artificial neural network and congestion approach of data envelopment analysis
Covid-19 virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) threatens the health of human beings worldwide, imposing a concern for the world and prompting governments to control the contagion. Although vaccination is a proper tool to control the transmission, the efficient allocatio...
Autores principales: | Yousefi, Saeed, Shabanpour, Hadi, Ghods, Kian, Saen, Reza Farzipoor |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798671/ https://www.ncbi.nlm.nih.gov/pubmed/36594043 http://dx.doi.org/10.1016/j.cie.2022.108933 |
Ejemplares similares
-
Using network data envelopment analysis to assess the sustainability and resilience of healthcare supply chains in response to the COVID-19 pandemic
por: Azadi, Majid, et al.
Publicado: (2022) -
A hybrid data envelopment analysis—artificial neural network prediction model for COVID-19 severity in transplant recipients
por: Revuelta, Ignacio, et al.
Publicado: (2021) -
How to Assess the Degree of Pulmonary Congestion in Patients with Congestive Heart Failure
por: Imamura, Teruhiko
Publicado: (2023) -
Estimation of Congestion in Free Disposal Hull Models Using Data Envelopment Analysis
por: Abbasi, M., et al.
Publicado: (2014) -
Biomarker Discovery Based on Hybrid Optimization Algorithm and Artificial Neural Networks on Microarray Data for Cancer Classification
por: Moteghaed, Niloofar Yousefi, et al.
Publicado: (2015)