New directions in artificial intelligence for public health surveillance

Research output: Contribution to journalArticlepeer-review


The next decade of disease surveillance research will require novel methods to effectively use massive quantities of complex, high-dimensional data. We summarize two recent approaches which deal with the increasing complexity and scale of health data, including the use of rich text data to detect emerging outbreaks with novel symptom patterns, and fast subset scan methods to efficiently identify the most relevant patterns in massive datasets.

Original languageEnglish (US)
Article number6163563
Pages (from-to)56-59
Number of pages4
JournalIEEE Intelligent Systems
Issue number1
StatePublished - Jan 2012


  • disease surveillance
  • event detection
  • public health surveillance
  • semantic scan statistic
  • spatial and subset scanning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence


Dive into the research topics of 'New directions in artificial intelligence for public health surveillance'. Together they form a unique fingerprint.

Cite this