Title: Optimization-Based Data Mining for Epilepsy Research
Speaker: Wanpracha Art Chaovalitwongse, Rutgers University
Date: December 5, 2005, 12:00 - 1:30 pm
Location: DIMACS Center, CoRE Bldg, Room 431, Rutgers University, Busch Campus, Piscataway, NJ
Abstract:
Uncontrolled epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. The main objective of this talk is to introduce novel optimization-based data mining approaches to the study of brain physiology, which might be able to revolutionize current diagnosis and treatment of epilepsy. Through quantitative analyses of electroencephalogram (EEG) recordings, a new data mining paradigm for feature selection and clustering is developed based on optimization techniques proposed in this paper. The experimental results in this study demonstrate that the proposed techniques can be used as a feature (electrode) selection technique to capture seizure pre-cursors. In addition, the proposed techniques will not only excavate hidden patterns/relationships in EEGs, but also will give a greater understanding of brain functions (as well as other complex systems) from a system perspective.
see: DIMACS Computational and Mathematical Epidemiology Seminar Series 2005 - 2006