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Synthetic Cardio Health Risk Factors Dataset
Patient Health Records & Digital Health
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£79.99
About
This synthetic CardioHealth Risk Dataset is designed to support educational and research applications in data science, machine learning, and healthcare analytics. The dataset provides detailed information about various health factors and cardiovascular conditions, aiming to help users analyze relationships between these factors and the risk of heart disease. It is useful for building predictive models, conducting health risk assessments, and exploring healthcare trends.
Dataset Features:
- Age: Age of the patient (in years).
- Sex: Gender of the patient (Female, Male).
- Chest Pain Type: Type of chest pain experienced (values 1–4, indicating varying levels of severity).
- BP (Blood Pressure): Patient’s blood pressure.
- Cholesterol: Cholesterol level of the patient.
- FBS over 120: Whether fasting blood sugar is greater than 120 mg/dl (False, True).
- EKG Results: Electrocardiographic test results (values 0–2).
- Max HR: Maximum heart rate achieved by the patient during exercise.
- Exercise Angina: Whether exercise-induced angina (chest pain) is present (No, Yes).
- ST Depression: Level of ST depression induced by exercise, relative to rest.
- Slope of ST: Slope of the peak exercise ST segment (values 1–3).
- Number of Vessels Fluor: Number of major vessels colored by fluoroscopy (values 0–3).
- Thallium: Thallium stress test result (values 3, 6, 7).
- Heart Disease: Presence or absence of heart disease (Presence, Absence).
Coverage:
Usage:
This dataset is valuable for various applications, including:
- Health Risk Analysis: To explore the relationship between cardiovascular risk factors and the likelihood of heart disease.
- Predictive Modeling: To build models that predict the presence or absence of heart disease based on patient data.
- Healthcare Research: To identify key risk factors associated with heart disease and cardiovascular conditions.
- Public Health Policy: To analyze health trends and guide interventions for preventing heart disease.
Coverage:
This dataset is synthetic and anonymized, ensuring that it is suitable for experimentation and learning without any real patient data concerns.
License:
CCO (Public Domain)
Who Can Use It:
- Data Science Learners: Ideal for practising data cleaning, manipulation, and building classification models.
- Healthcare Professionals and Researchers: Useful for understanding cardiovascular risks and contributing to health studies.
- Medical Analysts: For developing models to predict heart disease and evaluate treatment strategies.
- Public Health Officials: For analyzing trends and making data-driven decisions in cardiovascular health initiatives.
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