Recent developments in a variety of sectors, including health care, research and the direct-
to-consumer industry, have led to a dramatic increase in the amount of genomic data that …

Precision health leverages information from various sources, including omics, lifestyle,
environment, social media, medical records, and medical insurance claims to enable …

The sharing of genomic data holds great promise in advancing precision medicine and
providing personalized treatments and other types of interventions. However, these …

Patient genomes are interpretable only in the context of other genomes; however, genome
sharing enables discrimination. Thousands of monogenic diseases have yielded definitive …

Clinical research and practice in the 21st century is poised to be transformed by analysis of
computable electronic medical records and population-level genome-scale patient profiles …

The increasing number of health-data breaches is creating a complicated environment for
medical-data sharing and, consequently, for medical progress. Therefore, the development …

Machine learning models benefit from large and diverse datasets. Using such datasets,
however, often requires trusting a centralized data aggregator. For sensitive applications like …

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

Background One way of investigating how genes affect human traits would be with a
genome-wide association study (GWAS). Genetic markers, known as single-nucleotide …

Machine learning can have a major societal impact in computational biology applications. In
particular, it plays a central role in the development of precision medicine, whereby …