Jun won Lee, a PhD student in the Computer Science Department, recently returned from Washington, DC, where he presented a paper at the Annual Symposium of the American Medical Informatics Association (AMIA).  The AMIA Annual Symposium is a peer-reviewed conference and the largest and most comprehensive biomedical and health informatics symposium held anywhere in the world.  Jun and two of his fellow students in Dr. Giraud-Carrier's Data Mining Lab, Yao Huang Lin (an undergraduate student) and Matt Smith (a PhD student) submitted a paper in the student competition, the focus of which was the study of best practices related to knowledge discovery in health care data.  Out of papers submitted from around the world, the Data Mining Lab's paper was one of just a handful to be invited to present at the Symposium Data Mining Competition.  Jun's presentation at the symposium was well received; he ended up taking third place in the overall competition.

In their research for the paper, Jun, Yao, and Matt used data mining tools to derive useful information from the data and statistical information collected by the National Center for Health Statistics.  The students performed two experiments using decision tree and association rule modeling to find relationships in the data that may prove valuable to medical researchers.  They found several implicit relations among the data, showing, for example, a correlation between diabetes and wheezing in the chest, and high blood pressure and hearing disabilities. Jun, Yao, and Matt are excited and gratified by the recognition given to them by the AMIA; however, even more significant to them is the fact that the discoveries they made over the course of their research provide interesting insights that may open additional doors in the study of major diseases and risk factors for these diseases.