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Synthetic Osteoporosis Patient Records Dataset
Patient Health Records & Digital Health
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£179.99
About
The Synthetic Osteoporosis Prediction Dataset is designed for educational and research purposes to analyze health-related factors contributing to osteoporosis risk. It provides anonymized, synthetic data on individuals’ demographic, medical, and lifestyle factors.
Dataset Features
- age: Age of the individual (in years).
- gender: Gender of the individual (Male/Female).
- hormonal_changes: Presence of hormonal changes (Normal/Postmenopausal).
- family_history: Family history of osteoporosis (Yes/No).
- race_ethnicity: Race or ethnicity of the individual.
- body_weight: Weight classification (Underweight/Normal/Overweight).
- calcium_intake: Level of calcium intake (Adequate/Insufficient).
- vitamin_d_intake: Level of vitamin D intake (Sufficient/Insufficient).
- physical_activity: Physical activity level (Sedentary/Active).
- smoking: Smoking status (Yes/No).
- alcohol_consumption: Alcohol consumption level (None/Moderate/High).
- medical_conditions: Presence of medical conditions such as hyperthyroidism or rheumatoid arthritis.
- medications: Medications taken (e.g., corticosteroids, none).
- prior_fractures: History of prior fractures (Yes/No).
- osteoporosis: Osteoporosis diagnosis (Yes/No).
Distribution
Usage
This dataset can be used for the following applications:
- Osteoporosis Risk Prediction: Build models to predict osteoporosis based on demographic, medical, and lifestyle factors.
- Health Behavior Analysis: Study the impact of physical activity, calcium intake, and other factors on osteoporosis prevalence.
- Medical Research: Explore correlations between hormonal changes, body weight, and osteoporosis.
- Preventative Healthcare: Identify key predictors to inform early detection and prevention strategies.
- Policy and Decision Making: Provide insights into osteoporosis risk factors to guide public health initiatives.
Coverage
This synthetic dataset is anonymized and adheres to data privacy standards. It represents diverse demographics and health profiles, enabling broad applications in healthcare research and analysis.
License
CC0 (Public Domain)
Who Can Use It
- Data Scientists and Machine Learning Practitioners: For classification tasks related to osteoporosis prediction and risk analysis.
- Healthcare Researchers: To study risk factors and prevalence of osteoporosis in a synthetic population.
- Public Health Professionals: For insights into osteoporosis risk trends and preventative care.
- Educators and Students: As a teaching resource for analyzing health-related datasets and building predictive models.
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