Predicting of Stroke Risk Based On Clinical Symptoms Using the Logistic Regression Method
الموضوعات : مجله بین المللی ریاضیات صنعتی
M. GholamAzad
1
,
J. Pourmahmoud
2
,
A. R. Atashi
3
,
M. Farhoudi
4
,
R. Deljavan Anvari
5
1 - Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz, Iran.
2 - Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz, Iran.
3 - Department of E-Health, Virtual School, Tehran University of Medical Sciences, Tehran, Iran.
4 - Neurosciences Research Center, Tabriz university of medical sciences, Tabriz, Iran.
5 - Neurosciences Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
الکلمات المفتاحية: Prediction, Logistic Regression, Risk Factors, Classification, Stroke Risk,
ملخص المقالة :
Mathematical modeling is one of the feasible methods that can be used to solve real problems. Modeling can be done using a variety of methods, including statistical methods that can be used to predict a variety of events. Health is one of the most important areas of research in the world today. Among the various diseases in the health sector, this study concerns stroke which is the second leading cause of death and long-term human disability, that has led to doing this research. The main objective of this research is to design and to build a predictive model of stroke based on symptoms and clinical reports, whether or not stroke occurs in patients in the near future. Using logistic regression technology, the main pathogenic factors of stroke have been found and their incidence has been predicted. In this study, clinical information from 5411 patients was collected and, after applying the LR method, the predictive model was designed.
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