چکیده مقاله
Background:For enhancing the accuracy of diagnosis and the quality of patient care, Neural Networks NN method was approached in patients with Brain Stroke BS to predict the outcome by the risk factors Methods:In this prospective study, total of 332 brain stroke patients mean age 77 4 SD 10 4 years, 50 6% male from Imam Khomeini hospital, Ardabil, Iran, from 2004 to 2018, participated The NN was applied to predict the effects of risk factors on mortality The fitness and quality of models were measured by diagnostic indices Results:The most important predictors for BS mortality based on optimal model results were time interval after ten years, smoking, history of myocardial infarction, and age category The other independent variables sex, employment, residence, education level, former smoking, waterpipe smoking, history of heart disease, diabetes, oral contraceptive pill use, physical activates, history of cerebrovascular accident type, history of blood pressure history, history of hyperlipoproteinemia, were at moderate importance The finding of this study demonstrated that the accuracy rang of models is 81% 85%Conclusion:The NN strategy showed a satisfying presentation in the prediction of BS mortality based on the main risk factors with higher diagnostic accuracy
کلیدواژهها
نویسندگان
Mohammad Asghari Jafarabadi
Tabriz University of Medical Sciences, Tabriz, Iran۱
Nasrin Someeh
Tabriz University of Medical Sciences, Tabriz, Iran۱
Seyed Morteza Shamshirgarant
NeyshaburUniversity of Medical Sciences
Farshid Farzipoor
Tabriz University of Medical Sciences, Tabriz, Iran
شیوه ارجاع
Asghari Jafarabadi, Mohammad and Someeh, Nasrin and Shamshirgarant, Seyed Morteza and Farzipoor, Farshid,1398,The outcome in Patients Brain Stroke: A Neural Network Approach to predict utilizing the Subclinical Risk Factors,Second International Conference on Health and Health Promotion
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