PRIME-CVD：面向医学信息学教育的隐私保护心血管风险模拟数据集

PRIME-CVD is an open-source educational dataset developed by UNSW Health Big Data Research Center (CBDRH). It generates 50,000 simulated patient records via causal Directed Acyclic Graph (DAG), offering two versions: clean analysis-ready queue and real EMR-style "dirty" data. It supports teaching of causal inference, survival analysis, data cleaning, etc., while ensuring full privacy protection.

Medical informatics education faces a long-standing conflict between data access and privacy. Real EMR data is sensitive and regulated, hard to share; fully synthetic data lacks real-world complexity. PRIME-CVD is designed to solve this by providing privacy-safe, realistic simulated data.

• Clean Queue: 50k longitudinal records with variables like demographics (age, IRSD), lifestyle (smoking, BMI), clinical indicators (diabetes, HbA1c), cardiovascular status. Suitable for survival analysis, causal estimation.
• EMR-style Data: Relational tables with heterogeneities, missing values, unit inconsistencies (e.g., blood pressure in mmHg/kPa). Used for data cleaning, record linkage training.

• Causal DAG: Hand-built to model cardiovascular risk factor relationships (e.g., smoking→CVD, age→diabetes→CVD).
• Parameters: From authoritative sources (ABS, AIHW, published studies).
• Reproducibility: Deterministic generation—same seed produces identical data, enabling standard answers and fair comparisons.

• Resources: Series blogs/notebooks (dataset intro, assessment design, core concepts like discrimination/calibration) and Python/R quickstart notebooks.
• Use Cases: Educators (design assignments/exams), students (practice real data skills), researchers (test algorithms, validate methods).

Feature	Description
Privacy Safety	Fully synthetic data, no privacy leakage risk
Education-Oriented	Clear DAG and EMR artifact design
Reproducible	Deterministic process for dataset reconstruction
Dual Assets	Clean queue + dirty EMR covering full analysis flow
Open Access	Code, data, tutorials all open-source

PRIME-CVD innovates medical informatics education by balancing privacy and realism. Developed by UNSW CBDRH team (Dr. Nic Kuo, Dr. Marzia Hoque, Prof. Blanca Gallego, Prof. Louisa Jorm). Data available via figshare: Clean queue (https://doi.org/10.6084/m9.figshare.31395765.v1), EMR-style data (https://doi.org/10.6084/m9.figshare.31403028.v1).