Title: Using Artificial Intelligence Techniques in Epidemiology Research
Speaker: Masoumeh Tabaeh Izadi, McGill University, Clinical and Health Informatics Research Group
Date: Monday, December 10, 2007 12:00 - 1:30 pm
Location: DyDan Center, CoRE Bldg, Room 431, Rutgers University, Busch Campus, Piscataway, NJ
Abstract:
Artificial intelligence methods can support and assist optimal use of clinical and administrative knowledge in diverse perspectives from diagnostic assistance, and detection of epidemics, to improved efficiency of health care delivery processes. Probabilistic graphical models have been successfully used for many medical diagnosis problems. However, there have been few applications to epidemiological data where data mining methods play a significant role. In practice, what can be learned from epidemiological data can be very complex due to a great amount of uncertainty involved. Methods that can better assess and handle uncertainty are of great importance in this field. In this talk, I will discuss some applications of graphical models I have developed for epidemiology research. In particular, I will show how Partially Observable Markov Decision Processes (POMDPs) can be used in outbreak detection systems for improving credibility of statistical alarms.