Data-driven decision-making in modern healthcare underpins innovation and predictive
analytics in public health and clinical research. Synthetic data has shown promise in finance …

Data are central to research, public health, and in developing health information technology
(IT) systems. Nevertheless, access to most data in health care is tightly controlled, which …

You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Background Machine learning (ML) has made a significant impact in medicine and cancer
research; however, its impact in these areas has been undeniably slower and more limited …

Generative adversarial networks (GANs) implicitly learn the probability distribution of a
dataset and can draw samples from the distribution. This paper presents, Tabular GAN …

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or
mean imputation, only work under highly restrictive conditions, which are often not met in …

Information about us, our actions, and our preferences is created at scale through surveys or
scientific studies or as a result of our interaction with digital devices such as smartphones …

The federal statistical system is experiencing competing pressures for change. On the one
hand, for confidentiality reasons, much socially valuable data currently held by federal …

In many contexts, confidentiality constraints severely restrict access to unique and valuable
microdata. Synthetic data which mimic the original observed data and preserve the …

An up-to-date, comprehensive treatment of a classic text on missing data in statistics The
topic of missing data has gained considerable attention in recent decades. This new edition …