nezahatkorkmaz/heart-disease-dataset

❤️ 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.

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📊 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)

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🧠 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

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💡 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

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📁 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

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📬 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

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