Accessibility settings

This paper is in the following e-collection/theme issue:

Presentations, Abstracts, or Demonstrations (740)

Published on in Vol 5, No 1 (2013):

JMIR Publications logo: Advancing Digital Health & Open Science

Time of Arrival Analysis in NC DETECT to Find Clusters of Interest from Unclassified Patient Visit Records

Time of Arrival Analysis in NC DETECT to Find Clusters of Interest from Unclassified Patient Visit Records

Authors of this article:

Meichun Li1 ;   Wayne Loschen2 ;   Lana Deyneka3 ;   Howard Burkom2 ;   Amy Ising1 ;   Anna Waller1
The full text of this article is available as a PDF download by clicking here.
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Nobles M, Lall R, Mathes R, Neill D. Presyndromic surveillance for improved detection of emerging public health threats. Science Advances 2022;8(44) View
  2. Aronis J, Ye Y, Espino J, Hochheiser H, Michaels M, Cooper G. A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation. JMIR Public Health and Surveillance 2024;10:e57349 View
  3. Aronis J, Ye Y, Espino J, Michaels M, Hochheiser H, Cooper G. An evaluation of a Bayesian method to track outbreaks of known and novel influenza-like illnesses. Scientific Reports 2026;16(1) View