Using real-world evidence in biomedical research, an indispensable complement to clinical
trials, requires access to large quantities of patient data that are typically held separately by …

Multisite medical data sharing is critical in modern clinical practice and medical research.
The challenge is to conduct data sharing that preserves individual privacy and data utility …

Motivation Limited data access has hindered the field of precision medicine from exploring
its full potential, eg concerning machine learning and privacy and data protection rules. Our …

Background Machine learning and artificial intelligence have shown promising results in
many areas and are driven by the increasing amount of available data. However, these data …

Genome-wide association studies (GWAS) have revolutionized our understanding of the
genetic architecture of complex traits and diseases. GWAS summary statistics have become …

The long-lasting trend of medical informatics is to adapt novel technologies in the medical
context. In particular, incorporating artificial intelligence to support clinical decision-making …

Background Artificial intelligence (AI) has been successfully applied in numerous scientific
domains. In biomedicine, AI has already shown tremendous potential, eg, in the …

Indigenous peoples are under-represented in genomic datasets, which can lead to limited
accuracy and utility of machine learning models in precision health. While open data sharing …

Artificial intelligence (AI) and data sharing go hand in hand. In order to develop powerful AI
models for medical and health applications, data need to be collected and brought together …

The statistical power of genome-wide association studies (GWASs) is affected by the
effective sample size. However, the privacy and security concerns associated with individual …