Understanding Bias Through Imaginary Data Mapping

This chapter explores the construction and application of Generative Adversarial Networks (GANs) in data analysis with a focus on human health. It emphasizes the importance of using GANs to identify biases in training sets, which can enhance the development of more equitable machine learning systems.