Case Study 1: Stroke Patient Prediction

Context

According to the World Health Organization (WHO), stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths.

This dataset predicts whether a patient will likely get a stroke based on the input parameters like gender, age, various diseases, and smoking status. Each row in the data provides relevant information about the patient.

Attribute Information

1. id: unique identifier
2. gender: "Male," "Female," or "Other."
3. age: age of the patient
4. hypertension: 0 if the patient doesn't have hypertension, one if the patient has hypertension
5. heart_disease: 0 if the patient doesn't have any heart diseases, one if the patient has a heart disease
6. ever_married: "No" or "Yes."
7. work_type: "children", "Govt_jov", "Never_worked", "Private" or "Self-employed"
8. Residence_type: "Rural" or "Urban"
9. avg_glucose_level: average glucose level in blood
10. BMI: body mass index
11. smoking_status: "formerly smoked," "never smoked," "smokes," or "Unknown"*
12. stroke: 1 if the patient had a stroke or 0 if not

*Note: "Unknown" in smoking_status means that the information is unavailable for this patient

Acknowledgements

Click here to access healthcare-dataset-stroke-data.xls

Introduction and Abstract with references