Synthetic Healthcare Datasets
Synthetic datasets for machine learning, research, and healthcare data experimentation. All datasets are privacy-safe and designed for reproducible analysis.
Generate from blueprints
Synthetic type 2 diabetes trial with HbA1c as primary endpoint. Includes baseline demographics, visit schedule at weeks 0/12/24/52, and biomarker progression.
Synthetic oncology trial with overall survival and progression-free survival endpoints. Designed for cancer treatment efficacy simulation.
Synthetic dataset for 30-day hospital readmission prediction. Includes admission characteristics, discharge disposition, and readmission outcomes.
Synthetic cardiovascular outcomes trial. Includes MACE (major adverse cardiovascular events), LDL, blood pressure, and cardiac biomarkers.
Synthetic survival analysis dataset with time-to-event endpoints. Includes treatment groups, tumor staging, survival time, and event indicators for Kaplan-Meier and Cox regression.
Generic synthetic clinical trial with baseline and outcome measures. Designed for treatment efficacy comparison and primary endpoint analysis.
Synthetic longitudinal electronic health record cohort. Includes encounter types, diagnosis codes, and lab values over time for temporal analysis.
Synthetic healthcare claims and utilization dataset. Includes encounter types, admission diagnoses, ICD codes, and discharge dispositions for utilization analysis.
Synthetic metabolic disease cohort with HbA1c, LDL, and lab biomarkers. Designed for diabetes, dyslipidemia, and metabolic syndrome research.