Prediction of short-term outcome after subacute ischemic stroke using multiple layer perceptron neural network
10.3969/j.issn.1006-9771.2022.03.009
- VernacularTitle:采用多层感知器神经网络构建亚急性期缺血性脑卒中患者短期预后的预测模型
- Author:
Haifang LAI
1
;
Lin GU
2
;
Ya ZONG
1
;
Chuanxin NIU
1
;
Qing XIE
1
Author Information
1. 1. Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
2. 2. Shanghai Ruijin Rehabilitation Hospital, Shanghai 200023, China
- Publication Type:Journal Article
- Keywords:
ischemic stroke, subacute, multi-factor Logistic regression, multiple layer perceptron, neural network, prediction, short-term outcome
- From:
Chinese Journal of Rehabilitation Theory and Practice
2022;28(3):335-339
- CountryChina
- Language:Chinese
-
Abstract:
Objective To establish a predictive model using multiple layer perceptron (MLP) for short-term outcome after subacute ischemic stroke.Methods From January, 2019 to September, 2021, 60 readmission-inpatients in Department of Rehabilitation, Ruijin Hospital, Shanghai Jiaotong University School of Medicine were collected the clinical features of first admission (less than 30 days after attack), and the outcomes were assessed with modified Rankin Scale (MRS) three months after the first admission. The risk factors were screened with single factor analysis, and the short-term outcome predictive models were established with multi-factor Logistic regression and MLP. The predictive accuracy of both models was calculated, and the predictive effects were compared with Receiver Operating Characteristic (ROC) curve.Results For multi-factor Logistic regression, the predictive accuracy was 73.3%, and the area under ROC curve was 0.851. For MLP, the predictive accuracy was 88.9%, and the area under the ROC curve was 0.930.Conclusion The prediction of short-term outcome after subacute ischemic stroke can be done with MLP model.
