The Research of Influence Factors that Possibly lead to Stroke
DOI:
https://doi.org/10.54097/gxymy507Keywords:
Binary probit model; influence factors; stroke.Abstract
Although previous studies have demonstrated that the incidence of stroke is associated with hypertension, heart disease. In this research, the method Binary Probit Model is used to deal with the data from Kaggle named “Diabetes, Hypertension and Stroke Prediction” which was published 2015 for 70692 survey responses. It is concluded that although stroke has no connection with Gender, it has a relatively strong connection with heart disease and hypertension. Many of the factors having a possibly strong connection with stroke have never appeared in previous studies, such as heart disease which provides some new perspectives to study the pathogenesis. Advances in pathogenesis help improving the treatment of stroke and reach out for further research afterward. This paper uses Probit regression to study the relation between the three diseases from the data found in Kaggle, and the result seems to support a positive correlation between them which the three diseases are closely related to each other.
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