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 …

Synthetic datasets are gradually emerging as solutions for data sharing. Multiple synthetic
data generators have been introduced in the last decade fueled by advancement in machine …

Background: The exploitation of synthetic data in health care is at an early stage. Synthetic
data could unlock the potential within health care datasets that are too sensitive for release …

Modern machine and deep learning methods require large datasets to achieve reliable and
robust results. This requirement is often difficult to meet in the medical field, due to data …

In view of the various methodological developments regarding the protection of sensitive
data, especially with respect to privacy-preserving computation and federated learning, a …

Small area estimation is a research area in official and survey statistics of great practical
relevance for national statistical institutes and related organizations. Despite rapid …

Featured Application This study's findings hold significant implications for enhancing data
privacy and utility in healthcare analytics. By evaluating synthetic data generation methods …

Because of the complex production processes and technology-intensive operations that take
place in the aerospace and defense industry, introducing Industry 4.0 into the manufacturing …

Synthetic population is used in many transport models ranging from trip-based, hybrid trip,
tour-based, and activity-based models. As mobility decisions depend on both individuals' …

Ensuring the social equity of planning measures in social systems requires an
understanding of human dynamics, particularly how individual relationships, activities, and …