MATH Seminar

Title: Mining Medical Data To Improve Disease Diagnosis and Treatment
Seminar: Computer Science
Speaker: Carlos Ordonez of University of Houston
Contact: Li Xiong, lxiong@mathcs.emory.edu
Date: 2010-10-14 at 4:00PM
Venue: MSC W301
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Abstract: Abstract: Medical data sets have been generally analyzed with statistical techniques like regression, time series and statistical tests, among others. In this talk we will motivate how data mining techniques, traditionally used on large databases, can improve medical data analysis, where data sets are generally much smaller and attributes exhibit high variability. We will emphasize the importance of association rules and OLAP cubes. From a medical standpoint, we will summarize how our research helps heart disease and cancer diagnosis and treatment.\\ \\ Bio: Carlos Ordonez received a degree in applied mathematics and an M.S. degree in computer science, from UNAM University, Mexico, in 1992 and 1996, respectively. He got a Ph.D. degree in Computer Science from the Georgia Institute of Technology, in 2000. Dr Ordonez worked six years extending the Teradata DBMS with data mining algorithms. He is currently an Assistant Professor at the University of Houston. His research is centered on the integration of statistical and data mining techniques into database systems and their application to scientific problems.