Risk factor identification and prediction models for prolonged length of stay in hospital after acute ischemic stroke using artificial neural networks

BACKGROUND: Accurate estimation of prolonged length of hospital stay after acute ischemic stroke provides crucial information on medical expenditure and subsequent disposition. This study used artificial neural networks to identify risk factors and build prediction models for a prolonged length of s...

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Detalles Bibliográficos
Autores principales: Yang, Cheng-Chang, Bamodu, Oluwaseun Adebayo, Chan, Lung, Chen, Jia-Hung, Hong, Chien-Tai, Huang, Yi-Ting, Chung, Chen-Chih
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947790/
https://www.ncbi.nlm.nih.gov/pubmed/36846116
http://dx.doi.org/10.3389/fneur.2023.1085178

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947790/
https://www.ncbi.nlm.nih.gov/pubmed/36846116
http://dx.doi.org/10.3389/fneur.2023.1085178

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