Example Synthetic Diabetes Cohort Dataset Schema
A synthetic diabetes cohort dataset designed for machine learning, research, and healthcare data experimentation.
Variable Schema
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Data Preview
First 9 rows (preview only)
| patient_id | age | sex | treatment_group | baseline_measure | outcome_measure |
|---|---|---|---|---|---|
| P000001 | 71 | Female | treatment | 8.3 | 6.8 |
| P000002 | 43 | Male | control | 9 | 7.1 |
| P000003 | 59 | Female | treatment | 8.8 | 7.5 |
| P000004 | 67 | Male | control | 9.1 | 7.5 |
| P000005 | 44 | Male | control | 8.9 | 7 |
| P000006 | 65 | Male | treatment | 7.9 | 6.9 |
| P000007 | 51 | Female | treatment | 9.6 | 8.3 |
| P000008 | 53 | Male | control | 8.7 | 8 |
| P000009 | 51 | Female | treatment | 8.6 | 7.4 |
Reproduce This Dataset
Recreate this dataset in Python (Jupyter, Kaggle, or Google Colab) using the Syntherx SDK.
# Install Syntherx SDK
pip install syntherx
from syntherx import generate_dataset
df = generate_dataset(
blueprint="diabetes_hba1c_trial",
rows=5000
)
df.to_csv("diabetes_hba1c_trial.csv")Use Cases
- Machine learning training
- Healthcare research
- Synthetic data experimentation
Privacy-Safe Synthetic Dataset
- Contains no real patient data
- Generated using statistical simulation
- Designed for machine learning research