Big data in health and disease: Re-processing information for discovery and validation

Roseanne Yeung, Enrico Capobianco

Research output: Contribution to journalArticlepeer-review


A lot has been already said about the emerging role of big data in health and disease. Large scale data efforts are increasingly being undertaken in response to the advent of Personalized and Precision Medicine and in association with both the “omics revolution” and the Electronic Health Records centrality. big data have demonstrated that their complex characteristics bring both strength factors and bottlenecks to research problems widely identified, analyzed and reviewed across many sectors of medicine and public health. As the most significant feature of big data is “variety”, and this implies heterogeneity, our knowledge in complex disease contexts may substantially benefit from the fusion of different data types when a major role is assigned to harmonization and interoperability strategies. We discuss of an example, diabetes.

Original languageEnglish (US)
Article number5
JournalJournal of Medical Artificial Intelligence
Issue numberMarch
StatePublished - 2019


  • Dark matter
  • Diabetes
  • Electronic health records (EHR)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Medicine (miscellaneous)


Dive into the research topics of 'Big data in health and disease: Re-processing information for discovery and validation'. Together they form a unique fingerprint.

Cite this