Agent-based models of emergency departments generate synthetic EHR data to test whether machine learning models for length-of-stay prediction lose performance under mass casualty incident conditions.
Mooney, and Bradley A
2 Pith papers cite this work, alongside 87 external citations. Polarity classification is still indexing.
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Synthetic data generation in privacy-constrained medical domains shifts the engineering challenge from data availability to the elicitation, validation, and evolution of stakeholder-specific validity properties.
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Generating synthetic electronic health record data using agent-based models to evaluate machine learning robustness under mass casualty incidents
Agent-based models of emergency departments generate synthetic EHR data to test whether machine learning models for length-of-stay prediction lose performance under mass casualty incident conditions.
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Property-Driven Synthetic Data Engineering for Data-Scarce Software Systems: Reflections from the Breast Cancer Domain
Synthetic data generation in privacy-constrained medical domains shifts the engineering challenge from data availability to the elicitation, validation, and evolution of stakeholder-specific validity properties.