Comparative study of back propagation artificial neural networks and logistic regression model in predicting poor prognosis after acute ischemic stroke

Comparative study of back propagation artificial neural networks and logistic regression model in predicting poor prognosis after acute ischemic stroke

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.

Bibliographic Details
Main Authors: Liang Yaru, Li Qiguang, Chen Peisong, Xu Lingqing, Li Jiehua
Format: Article
Language:English
Published: De Gruyter 2019-04-01
Series:Open Medicine
Subjects:
back propagation artificial neural networks
logistic regression model
acute ischemic stroke
poor outcome
clinical variables
Online Access:https://doi.org/10.1515/med-2019-0030

Internet

https://doi.org/10.1515/med-2019-0030

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