Bayesian network anomaly pattern detection for disease outbreaks
Weng‐Keen Wong, Andrew Moore, Gregory F. Cooper, Michael M. Wagner · 2003
Early disease outbreak detection systems typically monitor health care data for irregularities by comparing the distribution of recent data against a baseline distribution. Determining the baseline is dicult due to the presence of dierent trends in health care data, such as trends caused by the day of week and by seasonal variations in temperature and weather. Creating the baseline distribution without taking these trends into account can lead to unacceptably high false positive counts and slow detection times.