Posts tagged: Health Data
What is the difference between selection bias and sampling bias?
A reference guide to the difference between selection bias and sampling bias in health data research, with worked examples of how each one distorts your results.
Synthetic Data in Machine Learning: Augmentation and Collapse
Exploring the use of synthetic data in machine learning, focusing on augmentation, model collapse, and the implications for health research using synthetic data.
What is a confounder, really?
A reference guide to what confounding means in health data research and how it is different from mediators and colliders.
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.
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.