Synthetic Heart Disease Dataset

Dataset Features:

• Age: Age of the patient at admission (in years).
• Country: Country of residence, specified as the USA.
• State: Random assignments of U.S. states for geographic analysis.
• Blood Pressure: Simulated values reflecting typical hypertension ranges (in mmHg).
• Cholesterol: Values adjusted to fall within common cholesterol levels (in mg/dL).
• BMI: Calculated to represent healthy to overweight classifications.
• Glucose Level: Simulated to represent fasting glucose levels (in mg/dL).
• Gender: Randomly assigned to simulate demographic diversity.
• Hospital: Randomly assigned hospitals to represent different healthcare facilities.
• Treatment Options: Various treatment methods including Physiotherapy, Medication, Surgery, Rehabilitation, and Counseling.
• Treatment Date: Randomly generated dates for when treatments were administered.
• Heart Disease: A binary indicator (0 = No, 1 = Yes) representing the presence of heart disease.

Data Distribution and Outliers:

Usage:

• Healthcare research: To explore trends and patterns in cardiovascular health, treatment efficacy, and patient demographics.
• Educational training: To teach data cleaning, transformation, and visualisation techniques specific to healthcare data.
• Predictive modelling: To develop models that predict heart disease risk based on various patient and demographic factors.

Coverage:

License:

Who can use it:

• Researchers and educators: For studies or teaching purposes in healthcare analytics and data science.
• Data science enthusiasts: For learning, practising, and applying healthcare data manipulation and analysis techniques.