Stroke Prediction

Strokes are a major global health problem, with millions of deaths occurring every year. The World Health Organization (WHO) has identified strokes as a serious medical concern. Strokes can have a devastating impact on the lives of those who experience them, as well as their families and communities. They can cause physical disability, cognitive impairment, and emotional distress, and often require extensive medical treatment and rehabilitation. Early detection and treatment of strokes is crucial for reducing their long-term effects and improving outcomes for patients. Research into the causes, prevention, and treatment of strokes is ongoing, with the goal of finding ways to reduce the global burden of this serious medical condition.

Dataset has been used form Kaggle.

Understanding the data

It is important to thoroughly analyze and understand the data and all of its features before using it to make predictions. By doing so, we may discover additional valuable features that can provide deeper insights and more accurate predictions.

Information about data frame

Seeing the ranging of values in data frame since we have only numeric data

Checking for null values

Checking the correlations

Cheking the BMI patienent count

We can interpolate date to fill the missing value

We Sort Average Glucose levels by Stroke to see if Stroke causes depend upon the average glucose level by the patient count

Let’s check between average glucose level and stroke

Making Model

Let’s drop irrelevant columns

Let’s prepare the model

Lets check model intercepts

Conclusion

Although our model has shown promising results, it needs to be further refined and improved before it can be deployed for practical use, as the current evaluation metrics do not indicate that it is ready for deployment. Nonetheless, this model serves as a successful proof of concept for using regression techniques for predicting strokes.

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You can visit my GitHub for this dashboard and other projects. Please feel free to reach me at kshp95@gmail.com. You can also reach me at my LinkedIn.