Synthetic data generation: State of the art in health care domain
Recent progress in artificial intelligence and machine learning has led to the growth of
research in every aspect of life including the health care domain. However, privacy risks and …
research in every aspect of life including the health care domain. However, privacy risks and …
The problem of fairness in synthetic healthcare data
Access to healthcare data such as electronic health records (EHR) is often restricted by laws
established to protect patient privacy. These restrictions hinder the reproducibility of existing …
established to protect patient privacy. These restrictions hinder the reproducibility of existing …
An ontology for fairness metrics
Recent research has revealed that many machine-learning models and the datasets they
are trained on suffer from various forms of bias, and a large number of different fairness …
are trained on suffer from various forms of bias, and a large number of different fairness …
Investigating synthetic medical time-series resemblance
Access to private medical data is restricted due to privacy laws, hindering research and real-
world use. Synthetic data generation provides a viable solution by generating data with high …
world use. Synthetic data generation provides a viable solution by generating data with high …
Downstream Fairness Caveats with Synthetic Healthcare Data
This paper evaluates synthetically generated healthcare data for biases and investigates the
effect of fairness mitigation techniques on utility-fairness. Privacy laws limit access to health …
effect of fairness mitigation techniques on utility-fairness. Privacy laws limit access to health …