8,763 synthetic patient records across 26 health and lifestyle features. Clinical metrics, demographic information, and behavioral factors are provided to facilitate the modeling of cardiovascular outcomes.
Use Cases
- Train a classification model to predict 'Heart Attack Risk' using 'Cholesterol' and 'Blood Pressure' columns
- Analyze the correlation between 'Physical Activity Days Per Week' and cardiovascular health outcomes
- Evaluate the impact of 'Stress Level' and 'Sleep Hours Per Day' on heart attack probability
Strengths
- 8,763 rows of synthetic patient data
- 26 features including 'Cholesterol', 'Heart Rate', and 'BMI'
- Binary target variable 'Heart Attack Risk' for classification tasks