Conference proceeding
Ensemble based data fusion from parietal region event related potentials for early diagnosis of Alzheimer's disease
2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, p2408
IEEE International Joint Conference on Neural Networks (IJCNN)
01 Jan 2007
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
As a natural consequence of steady increase of average population age in developed countries, Alzheimer's disease is becoming an increasingly important public health concern. The financial and emotional toll of the disease is exacerbated with lack of standard diagnostic procedures available at the community clinics and hospitals, where most patients are evaluated. In our recent preliminary results, we have reported that the event related potentials (ERPs) of the electroencephalogram can be used to train an ensemble-based classifier for automated diagnosis of Alzheimer's disease. In this study, we present an updated alternative approach by combining complementary information provided by ERPs obtained from several parietal region electrodes. The results indicate that ERPs obtained from parietal region of the cortex carry substantial complementary diagnostic information. Specifically, the diagnostic ability of such an approach is substantially better, compared to the performance obtained by using data from any of the individual electrodes alone. Furthermore, the diagnostic performance of the proposed approach compares very favorably to that obtained at community clinics and hospitals.
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Details
- Title
- Ensemble based data fusion from parietal region event related potentials for early diagnosis of Alzheimer's disease
- Creators
- Brian A. Balut - Rowan Univ, Elect & Comp Engn Dept, Signal Processing & Pattern Recognit Lab, Glassboro, NJ 08028 USAMatthew T. Karnick - Rowan Univ, Elect & Comp Engn Dept, Signal Processing & Pattern Recognit Lab, Glassboro, NJ 08028 USADeborah Green - Drexel Univ, Dept Psychol, Philadelphia, PA 19104 USAJohn Kounios - Drexel UniversityChristopher M. Clark - Univ Penn, Dept Neurol, Philadelphia, PA 19104 USARobi Polikar - Rowan Univ, Elect & Comp Engn Dept, Signal Processing & Pattern Recognit Lab, Glassboro, NJ 08028 USAIEEE
- Publication Details
- 2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, p2408
- Series
- IEEE International Joint Conference on Neural Networks (IJCNN)
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- ECS-0239090 / National Science Foundation; National Science Foundation (NSF) P30 AG10 124 - RO I AG022272 / National Institute on Aging of the National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute on Aging (NIA)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Psychology
- Identifiers
- 991019170450504721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering