Comparative Study of Back Propagation Artificial Neural Networks and Logistic Regression Model in Predicting Poor Prognosis after Acute Ischemic Stroke

OBJECTIVE: To investigate the predictive value of clinical variables on the poor prognosis at 90-day follow-up from acute stroke onset, and compare the diagnostic performance between back propagation artificial neural networks (BP ANNs) and Logistic regression (LR) models in predicting the prognosis...

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Detalles Bibliográficos
Autores principales: Liang, Yaru, Li, Qiguang, Chen, Peisong, Xu, Lingqing, Li, Jiehua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6463818/
https://www.ncbi.nlm.nih.gov/pubmed/30997395
http://dx.doi.org/10.1515/med-2019-0030

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6463818/
https://www.ncbi.nlm.nih.gov/pubmed/30997395
http://dx.doi.org/10.1515/med-2019-0030

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