This paper provides an overview of recent
developments in big data in the context of biomedical and health
informatics. It outlines the key characteristics of big data and
how medical and health informatics, translational bioinformatics,
sensor informatics, and imaging informatics will benefit from
an integrated approach of piecing together different aspects of
personalized information from a diverse range of data sources,
both structured and unstructured, covering genomics, proteomics,
metabolomics, as well as imaging, clinical diagnosis, and long-term
continuous physiological sensing of an individual. It is expected that
recent advances in big data will expand our knowledge for testing
new hypotheses about disease management from diagnosis to prevention
to personalized treatment. The rise of big data, however,
also raises challenges in terms of privacy, security, data ownership,
data stewardship, and governance. This paper discusses some of
the existing activities and future opportunities related to big data
for health, outlining some of the key underlying issues that need to
be tackled.
Index Terms—Big data, bioinformatics, health informatics, medical
imaging, medical informatics, precision medicine, sensor
informatics, social health