Cardiology Ward Dataset 2026
Description
This synthetic cardiovascular registry dataset was developed to simulate a real-world tertiary hospital cardiology database from 2023 for educational, research training, and data analysis purposes. The dataset contains anonymized fictional records of 120 patients presenting with various cardiovascular conditions, including acute coronary syndrome, heart failure, arrhythmia, pulmonary embolism, hypertensive emergency, myocarditis, and valvular heart disease. Variables included demographic characteristics, cardiovascular risk factors, presenting symptoms, laboratory investigations, electrocardiographic findings, echocardiographic parameters, treatment interventions, intensive care utilization, length of hospitalization, and clinical outcomes. Additional registry-style variables such as readmission risk score, audit flags, severity classification, and mortality prediction indicators were incorporated to mimic the complexity of institutional clinical registries commonly used in cardiovascular quality improvement and observational research. The dataset was intentionally structured with advanced formatting, multi-variable relationships, and realistic clinical variability to support practice in epidemiological analysis, biostatistics, machine learning modeling, dashboard creation, and manuscript preparation. All data are fully synthetic and do not contain any real patient information.
Files
Institutions
- Duke-NUS Medical SchoolSG.01, Singapore