metadata
license: mit
❤️ Heart Disease Dataset (Enhanced with Feature Engineering)
📌 Overview
This dataset is an enhanced version of the classic UCI Heart Disease dataset, enriched with extensive feature engineering to support advanced data analysis and machine learning applications.
In addition to the original clinical features, several derived variables have been introduced to provide deeper insights into cardiovascular risk patterns. These engineered features allow for improved predictive modeling and more robust exploratory data analysis.
📊 Original Features
| Column | Description |
|---|---|
age |
Age of the patient (years) |
sex |
Gender (1 = male, 0 = female) |
cp |
Chest pain type (1 = typical angina, 2 = atypical angina, 3 = non-anginal pain, 4 = asymptomatic) |
trestbps |
Resting blood pressure (mm Hg) |
chol |
Serum cholesterol (mg/dl) |
fbs |
Fasting blood sugar > 120 mg/dl (1 = true, 0 = false) |
restecg |
Resting electrocardiographic results (0 = normal, 1 = ST-T abnormality, 2 = left ventricular hypertrophy) |
thalach |
Maximum heart rate achieved |
exang |
Exercise-induced angina (1 = yes, 0 = no) |
oldpeak |
ST depression induced by exercise |
slope |
Slope of the peak exercise ST segment (1 = upsloping, 2 = flat, 3 = downsloping) |
ca |
Number of major vessels colored by fluoroscopy |
thal |
Thalassemia (3 = normal, 6 = fixed defect, 7 = reversible defect) |
num |
Diagnosis of heart disease (0 = no disease, 1-4 = disease severity levels) |
🧠 Engineered Features
| Feature | Description |
|---|---|
age_group |
Age category (30s, 40s, 50s, 60s) |
cholesterol_level |
Cholesterol status (low, normal, high) |
bp_level |
Blood pressure status (low, normal, high) |
risk_score |
Composite risk score: (age * chol / 1000 + trestbps / 100) |
symptom_severity |
Severity index based on symptoms: (cp * oldpeak) |
log_chol |
Logarithm of cholesterol level |
log_trestbps |
Logarithm of resting blood pressure |
age_squared |
Square of patient age |
chol_squared |
Square of cholesterol level |
age_thalach_ratio |
Ratio of max heart rate to age (plus 1) |
risk_factor |
Advanced risk factor: (cp * oldpeak * thal) |
missing_values |
Count of missing values in ca and thal |
chol_trestbps_ratio |
Ratio of cholesterol to resting BP |
log_thalach_chol |
Log of (heart rate × cholesterol) |
symptom_zscore |
Z-score of symptom severity |
avg_chol_by_age_group |
Average cholesterol for corresponding age group |
thalach_chol_diff |
Difference between max heart rate and cholesterol |
symptom_severity_diff |
Deviation from average symptom severity by age group |
age_chol_effect |
Product of age and cholesterol |
thalach_risk_effect |
Product of max heart rate and risk score |
age_trestbps_effect |
Product of age and resting BP |
chol_risk_ratio |
Ratio of cholesterol to risk score |
💡 Use Cases
- Cardiovascular risk prediction using machine learning
- Exploratory data analysis for medical research
- Feature selection and dimensionality reduction tutorials
- Educational purposes in data science and healthcare analytics
- Model interpretability studies using engineered variables
📁 File Info
- Format: CSV or DataFrame (depending on hosting)
- Instances: ~300 patients
- License: MIT (Open Source)
- Source: Based on UCI Heart Disease Dataset + custom engineered features
📬 Citation & Contact
If you use this dataset in your research or application, please consider citing the original UCI dataset and giving credit to this enhanced version's author.
Author: nezahatkk
GitHub: https://github.com/nezahatkk