The Community for Technology Leaders
RSS Icon
Issue No.01 - January/February (2012 vol.27)
pp: 56-59
Daniel B. Neill , Event and Pattern Detection Laboratory, H.J. Heinz III College, Carnegie Mellon University
<p>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.</p>
event detection; disease surveillance; public health surveillance; spatial and subset scanning; semantic scan statistic
Daniel B. Neill, "New Directions in Artificial Intelligence for Public Health Surveillance", IEEE Intelligent Systems, vol.27, no. 1, pp. 56-59, January/February 2012, doi:10.1109/MIS.2012.18
1. M. Kulldorff, "Prospective Time-Periodic Geographical Disease Surveillance Using a Scan Statistic," J. Royal Statistical Society A, vol. 164, 2001, pp. 61–72.
2. M. Kulldorff et al., "Multivariate Scan Statistics for Disease Surveillance," Statistics in Medicine, vol. 26, no. 8, 2007, pp. 1824–1833.
3. G.F. Cooper et al., "Bayesian Biosurveillance of Disease Outbreaks," Proc. 20th Conf. Uncertainty in Artificial Intelligence, ACM, 2004, pp. 94–103.
4. D.B. Neill and G.F. Cooper, "A Multivariate Bayesian Scan Statistic for Early Event Detection and Characterization," Machine Learning, vol. 79, 2010, pp. 261–282.
5. W.R. Hogan et al., "The Bayesian Aerosol Release Detector: An Algorithm for Detecting and Characterizing Outbreaks Caused by an Atmospheric Release of Bacillus Anthracis," Statistics in Medicine, vol. 26, 2007, pp. 5225–5252.
6. T. Fawcett and F. Provost, "Activity Monitoring: Noticing Interesting Changes in Behavior," Proc. 5th Int'l Conf. Knowledge Discovery and Data Mining (KDD 99), ACM, 1999, pp. 53–62.
7. M. Wagner et al., "A National Retail Data Monitor for Public Health Surveillance," Morbidity and Mortality Weekly Report, vol. 53, 2004, pp. 40–42.
8. W.W. Chapman et al., "Classifying Free–Text Chief Complaints into Syndromic Categories with Natural Language Processing," Artificial Intelligence in Medicine, vol. 33, no. 1, 2005, pp. 31–40.
9. Y. Liu and D.B. Neill, "Detecting Previously Unseen Outbreaks with Novel Symptom Patterns," Emerging Health Threats J., vol. 4, 2011, in press.
10. D. Blei, A. Ng, and M. Jordan, "Latent Dirichlet Allocation," J. Machine Learning Research, vol. 3, 2003, pp. 993–1022.
11. D.B. Neill, "Fast Subset Scan for Spatial Pattern Detection," J. Royal Statistical Society B, 2011, to be published.
12. D.B. Neill, E. McFowland III, and H. Zheng, "Fast Subset Scan for Multivariate Spatial Biosurveillance," Emerging Health Threats J., vol. 4, 2011, p. s42.
13. E. McFowland III, S. Speakman, and D.B. Neill, "Fast Generalized Subset Scan for Anomalous Pattern Detection," Proc. INFORMS Annual Conf., 2010.
14. S. Speakman and D.B. Neill, "Fast Graph Scan for Scalable Detection of Arbitrary Connected Clusters," Proc. Int'l Soc. Disease Surveillance Annual Conf., 2009.
15. T. Tango and K. Takahashi, "A Flexibly Shaped Spatial Scan Statistic for Detecting Clusters," Int'l J. Health Geographics, vol. 4, 2005, p. 11.
31 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool