Posts tagged: PhD
Fairness and Bias Amplification in Synthetic Data
Explore how synthetic data can amplify existing biases and affect fairness in health research. Learn why this happens and how it differs from representativeness.
Bias in Synthetic Data
An exploration of bias in synthetic data and its implications for health research.
What Do We Mean by Bias in Health Data Research?
A reference guide to what bias means in health data research and the distinct types you meet in electronic health records and other health datasets.
How Private is Synthetic Data? Understanding the Tradeoff with Utility
Synthetic data is a powerful tool for health research, but it comes with a tradeoff between privacy and utility. This blog explores what this means for researchers and how to navigate the tradeoff.
How Do We Measure the Utility of Synthetic Data?
A practical guide to some of the metrics you can use to evaluate the utility of synthetic data.
Is your Synthetic Data actually private?
A practical guide to the three privacy risks in synthetic data, the metrics that quantify them, and why no single number tells you whether your data is safe.
Synthetic Data: The Complete Series
The jumping off point for my synthetic data series, covering the basics of synthetic data generation and its applications.
How Synthetic Data Is Used in Healthcare, Research and Beyond
Explore real-world use cases for synthetic data in healthcare, clinical trials, finance and more.
Multiple Imputation and Perturbation: Why They're Not Built for Synthetic Data
This blog explores why multiple imputation and perturbation are not suitable for generating synthetic data.